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zhU-5<;6Gyi+q(XS>pw!^KVtsdy8b_e>mS?xe_i>L^N&i7$QvOM6I&~DT_@yan4*cD zIh@MQ<|X{+VLKdwyiYO3#dfrT8{%SfPyslh$bWyls32f4Cz$HzNB?{QkToEGzNip? z(2(~7C^QhV*Hu0!7@5KH&wW8K4wUggTp(l?%qx6c5M)B-KhwZ~pP4nU(2yl7QD`6# z5{WB(VB`u=Xkg@*6<7G6Kot4FTu>DGAjtBXSNlScB~ejmKrYn2e}NwaS(Fu}FBFP0 z9`Z&KWjrVVgn~U307a!C^MYQT0}A?!@gQK-Ibc8(8d8-g*uyxvuF4DmKp2a1jWAWq;_{UT{FR2m3?G6x6(Ly->z1*6CZg2Arp z2msq00c!oFz{z0@jtH@4CF$=0L+PsDH!xK0$k|}2L1&N zib{ikQRjgEg)A@>e*=JFu&cHP0CRy+Fh$lmy=p@Mq#ykS4aMI85Fkp706>u7UtKQ* zj1rrW=7$oS01zk#YTv(D8w7@`UkDc}&QJ~x6#SqZFcdq00#N0H0#W=D0OdsSOC*g8 z#r~imR6m0LEG~S-4xo^~7!S&UVrx(+7?lP?Ry4jk9v1)wKPVTnIP?|1zlae47yu<06%{-_4D<|zKYD#3_$TqWbS4ZeIU&bMLsUn{TF}?O(J5~94ImaIRN0R_JTYC175`sxx=I2jHIE+4CDZz?1MlK zWZ=EBUL*}=UjTBT?s-5CC`ueh(vStU|ExD4Qk7Tn=-2?G5*ef<6Kk^f(FXj1*-=PJmvy?XfbfR)%{{skb(sTd- literal 0 HcmV?d00001 From 57b1ae637df5c9e4ff2ecc9522ca5d63bcf7ddab Mon Sep 17 00:00:00 2001 From: kiran Date: Sun, 3 May 2026 00:14:09 +1000 Subject: [PATCH 2/4] Sprint 2: augmentation benchmarking notebook --- Sprint2_Augmentation_KD.ipynb | 1254 +++++++++++++++++++++++++++++++++ 1 file changed, 1254 insertions(+) create mode 100644 Sprint2_Augmentation_KD.ipynb diff --git a/Sprint2_Augmentation_KD.ipynb b/Sprint2_Augmentation_KD.ipynb new file mode 100644 index 000000000..fe7b4ac22 --- /dev/null +++ b/Sprint2_Augmentation_KD.ipynb @@ -0,0 +1,1254 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "403b06f0-ae62-4fe7-924b-30aa74b435d3", + "metadata": {}, + "source": [ + "# Sprint 2: Augmentation Benchmarking\n", + "\n", + "# Introduction\n", + "\n", + "This notebook presents a limited augmentation benchmarking study using selected methods identified in the Sprint 1 augmentation strategy survey. The aim is to evaluate the impact of different augmentation techniques on model performance and determine which methods should be used in future development.\n", + "\n", + "The methods tested include:\n", + "\n", + "- Baseline (no augmentation)\n", + "- Time stretching\n", + "- Pitch shifting\n", + "- Gaussian noise injection\n", + "- SpecAugment\n", + "\n", + "To improve the technical quality of the model, a Convolutional Neural Network (CNN) is used with Mel spectrogram inputs. This approach is more suitable for audio classification, as Mel spectrograms represent both time and frequency information, allowing the CNN to learn more meaningful patterns compared to simpler models.\n", + "\n", + "Each augmentation method is compared against the same no-augmentation baseline using identical dataset splits, CNN architecture, and training parameters. This ensures a fair and controlled comparison where only the augmentation method is changed." + ] + }, + { + "cell_type": "markdown", + "id": "cc3fa79e-a470-4b07-8483-7358fdf42faf", + "metadata": {}, + "source": [ + "## Advanced CNN Benchmark\n", + "\n", + "In Sprint 1, several augmentation techniques were analysed to improve model performance, including SpecAugment, time stretching, pitch shifting, and Gaussian noise injection.\n", + "\n", + "These include time stretching, pitch shifting, Gaussian noise injection, SpecAugment, and a combined Noise + SpecAugment approach." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "8df77736-dc50-4cc1-a420-fce6d7db887d", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "import os\n", + "import random\n", + "import numpy as np\n", + "import librosa\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.preprocessing import LabelEncoder\n", + "from sklearn.metrics import accuracy_score, f1_score, confusion_matrix, ConfusionMatrixDisplay\n", + "\n", + "import tensorflow as tf\n", + "from tensorflow.keras.models import Sequential\n", + "from tensorflow.keras.layers import Conv2D, MaxPooling2D, BatchNormalization, Dropout, Dense, Flatten\n", + "from tensorflow.keras.utils import to_categorical\n", + "\n", + "# Reproducibility\n", + "SEED = 42\n", + "random.seed(SEED)\n", + "np.random.seed(SEED)\n", + "tf.random.set_seed(SEED)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "3e583517-bcf5-4013-82b5-d08658bb8683", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Dataset exists: True\n", + "Number of categories: 123\n" + ] + } + ], + "source": [ + "#Dataset path check\n", + "\n", + "dataset_path = r\"C:\\Users\\kiran\\Projects\\Project-Echo\\src\\Prototypes\\data\\data_files\"\n", + "\n", + "print(\"Dataset exists:\", os.path.exists(dataset_path))\n", + "print(\"Number of categories:\", len(os.listdir(dataset_path)))" + ] + }, + { + "cell_type": "markdown", + "id": "0684d76a-1252-492c-9504-a6a2535d56c3", + "metadata": {}, + "source": [ + "### Controlled Dataset Selection\n", + "\n", + "To ensure a fair and manageable experiment, a subset of the dataset is selected. Five categories are used, and a fixed number of audio files are taken from each category.\n", + "\n", + "This approach reduces computational load while maintaining a balanced dataset. It also supports a controlled comparison, where all augmentation methods are evaluated under the same conditions." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "01988136-2aef-4872-8312-9d115658bbe9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Selected categories: ['Acanthiza chrysorrhoa', 'Acanthiza lineata', 'Acanthiza nana', 'Acanthiza pusilla', 'Acanthiza reguloides']\n", + "Total files selected: 186\n" + ] + } + ], + "source": [ + "# Select Small Controlled Dataset\n", + "\n", + "categories = sorted(os.listdir(dataset_path))[:5] # using 5 classes to improve the robustness of the benchmark\n", + "max_files_per_category = 40\n", + "\n", + "audio_files = []\n", + "labels = []\n", + "\n", + "for category in categories:\n", + " category_path = os.path.join(dataset_path, category)\n", + "\n", + " if os.path.isdir(category_path):\n", + " files = [\n", + " os.path.join(category_path, file)\n", + " for file in os.listdir(category_path)\n", + " if file.lower().endswith((\".wav\", \".mp3\"))\n", + " ]\n", + "\n", + " files = files[:max_files_per_category]\n", + "\n", + " for file in files:\n", + " audio_files.append(file)\n", + " labels.append(category)\n", + "\n", + "print(\"Selected categories:\", categories)\n", + "print(\"Total files selected:\", len(audio_files))\n" + ] + }, + { + "cell_type": "markdown", + "id": "2397940e-a96b-42a9-8be6-17d532654d76", + "metadata": {}, + "source": [ + "### Audio Augmentation Functions\n", + "\n", + "The following functions implement selected augmentation techniques identified in Sprint 1. Each method is applied independently to evaluate its impact on model performance compared to the no-augmentation baseline.\n", + "\n", + "A combined augmentation method (noise + SpecAugment) is also included to introduce additional variability and increase the complexity of the benchmark." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "170dc988-e2a5-42e4-8fef-95b9fcec4284", + "metadata": {}, + "outputs": [], + "source": [ + "# Audio Augmentation Functions\n", + "\n", + "def apply_augmentation(y, sr, augment_type=\"none\"):\n", + " if augment_type == \"none\" or augment_type == \"specaugment\":\n", + " return y\n", + "\n", + " elif augment_type == \"time_stretch\":\n", + " return librosa.effects.time_stretch(y, rate=1.1)\n", + "\n", + " elif augment_type == \"pitch_shift\":\n", + " return librosa.effects.pitch_shift(y, sr=sr, n_steps=2)\n", + "\n", + " elif augment_type == \"noise\":\n", + " noise = np.random.normal(0, 0.005, len(y))\n", + " return y + noise\n", + "\n", + " elif augment_type == \"noise_specaugment\":\n", + " noise = np.random.normal(0, 0.005, len(y))\n", + " return y + noise\n", + "\n", + " return y" + ] + }, + { + "cell_type": "markdown", + "id": "4737d6e2-ff06-4edf-9627-a81da4ce5a81", + "metadata": {}, + "source": [ + "### Mel Spectrogram Feature Extraction\n", + "\n", + "Audio signals are converted into Mel spectrograms to capture both time and frequency information in a form suitable for model training.\n", + "\n", + "At this stage, SpecAugment is applied by masking selected regions of the spectrogram. This helps the model learn more general patterns instead of relying on specific details, which improves robustness and performance on unseen data." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "f58c6a92-363d-4a56-90b7-c233506e6886", + "metadata": {}, + "outputs": [], + "source": [ + "# Mel Spectrogram Feature Extraction\n", + "\n", + "def extract_mel_spectrogram(file_path, augment_type=\"none\", max_pad_len=216):\n", + " y, sr = librosa.load(file_path, sr=22050, duration=5)\n", + "\n", + " y = apply_augmentation(y, sr, augment_type)\n", + "\n", + " mel = librosa.feature.melspectrogram(\n", + " y=y,\n", + " sr=sr,\n", + " n_mels=128,\n", + " n_fft=2048,\n", + " hop_length=512\n", + " )\n", + "\n", + " mel_db = librosa.power_to_db(mel, ref=np.max)\n", + " \n", + " # Apply SpecAugment on spectrogram\n", + " if augment_type in [\"specaugment\", \"noise_specaugment\"]:\n", + " mel_db = apply_specaugment(mel_db)\n", + "\n", + " # Pad or truncate to fixed size\n", + " if mel_db.shape[1] < max_pad_len:\n", + " pad_width = max_pad_len - mel_db.shape[1]\n", + " mel_db = np.pad(mel_db, pad_width=((0, 0), (0, pad_width)), mode=\"constant\")\n", + " else:\n", + " mel_db = mel_db[:, :max_pad_len]\n", + "\n", + " return mel_db" + ] + }, + { + "cell_type": "markdown", + "id": "e9e70531-45ab-428e-a04c-ade1bed1b417", + "metadata": {}, + "source": [ + "### SpecAugment Implementation\n", + "\n", + "SpecAugment is applied to the Mel spectrogram by masking random regions along the time and frequency axes. \n", + "\n", + "This simulates missing or distorted parts of the audio signal, forcing the model to rely on broader patterns rather than specific features. As a result, it improves robustness and helps reduce overfitting." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "fabe8db7-cd62-4ae6-8fd7-62d0bbaf2cce", + "metadata": {}, + "outputs": [], + "source": [ + "# SpecAugment Function\n", + "\n", + "def apply_specaugment(spec, time_mask_param=25, freq_mask_param=15):\n", + " spec = spec.copy()\n", + " mask_value = spec.min()\n", + "\n", + " freq_mask = np.random.randint(1, freq_mask_param) # Apply frequency masking\n", + " f0 = np.random.randint(0, max(1, spec.shape[0] - freq_mask))\n", + " spec[f0:f0 + freq_mask, :] = mask_value\n", + "\n", + " time_mask = np.random.randint(1, time_mask_param) # Apply time masking\n", + " t0 = np.random.randint(0, max(1, spec.shape[1] - time_mask))\n", + " spec[:, t0:t0 + time_mask] = mask_value\n", + "\n", + " return spec" + ] + }, + { + "cell_type": "markdown", + "id": "36b84cb2-507f-4134-89c5-c871bbffbf97", + "metadata": {}, + "source": [ + "### Dataset Preparation for Augmentation Benchmark\n", + "\n", + "For each augmentation method, the dataset is prepared using the same set of audio files and labels. The selected augmentation is applied during feature extraction, ensuring that only the augmentation method changes while all other factors remain consistent.\n", + "\n", + "This supports a controlled comparison, as required in the task, where the model architecture, dataset, and training parameters remain the same for all experiments." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "bf0e838d-6017-449d-a427-1996a7ecf4a4", + "metadata": {}, + "outputs": [], + "source": [ + "# Prepare Dataset for One Augmentation Method\n", + "\n", + "def prepare_dataset(augment_type=\"none\"):\n", + " X = []\n", + " y_data = []\n", + "\n", + " for file_path, label in zip(audio_files, labels):\n", + " try:\n", + " # Extract spectrogram with augmentation applied\n", + " spec = extract_mel_spectrogram(file_path, augment_type)\n", + "\n", + " X.append(spec)\n", + " y_data.append(label)\n", + "\n", + " except Exception as e:\n", + " print(\"Skipped:\", file_path, e)\n", + "\n", + " # Convert to numpy array\n", + " X = np.array(X)\n", + " X = X[..., np.newaxis] # Add channel dimension for CNN\n", + "\n", + " # Encode labels\n", + " label_encoder = LabelEncoder()\n", + " y_encoded = label_encoder.fit_transform(y_data)\n", + " y_encoded = to_categorical(y_encoded)\n", + "\n", + " return X, y_encoded, label_encoder" + ] + }, + { + "cell_type": "markdown", + "id": "821b2be8-70f8-420b-a5e5-5d1b763c01ea", + "metadata": {}, + "source": [ + "### CNN Model Architecture\n", + "\n", + "A Convolutional Neural Network (CNN) is used to classify the Mel spectrogram inputs. The model consists of multiple convolutional layers with increasing filter sizes to capture different levels of audio features.\n", + "\n", + "Batch normalisation and dropout are included to improve training stability and reduce overfitting. Max pooling layers are used to reduce spatial dimensions while preserving important patterns.\n", + "\n", + "The final dense layer uses a softmax activation function to produce class probabilities for multi-class classification." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "2d6f55a5-001f-4106-b704-080664875845", + "metadata": {}, + "outputs": [], + "source": [ + "# CNN Model\n", + "\n", + "def build_cnn_model(input_shape, num_classes):\n", + " model = Sequential([\n", + " Conv2D(32, (3, 3), activation=\"relu\", input_shape=input_shape),\n", + " BatchNormalization(),\n", + " MaxPooling2D((2, 2)),\n", + " Dropout(0.25),\n", + "\n", + " Conv2D(64, (3, 3), activation=\"relu\"),\n", + " BatchNormalization(),\n", + " MaxPooling2D((2, 2)),\n", + " Dropout(0.25),\n", + "\n", + " Conv2D(128, (3, 3), activation=\"relu\"),\n", + " BatchNormalization(),\n", + " MaxPooling2D((2, 2)),\n", + " Dropout(0.30),\n", + "\n", + " Flatten(),\n", + "\n", + " Dense(128, activation=\"relu\"),\n", + " Dropout(0.40),\n", + "\n", + " Dense(num_classes, activation=\"softmax\")\n", + " ])\n", + "\n", + " model.compile(\n", + " optimizer=\"adam\",\n", + " loss=\"categorical_crossentropy\",\n", + " metrics=[\"accuracy\"]\n", + " )\n", + "\n", + " return model" + ] + }, + { + "cell_type": "markdown", + "id": "88739fb4-306f-4a00-8052-58f048d69fd8", + "metadata": {}, + "source": [ + "### Benchmark Function\n", + "\n", + "This function runs the controlled benchmarking process for each augmentation method.\n", + "\n", + "The dataset is split into training, validation, and test sets before augmentation is applied. Augmentation is only applied to the training data, while validation and test data remain unchanged. This creates a fair comparison because the model is evaluated on clean unseen data.\n", + "\n", + "The same CNN architecture, dataset split, training settings, and evaluation metrics are used for each experiment. This ensures that the only changing factor is the augmentation method being tested." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "fb513d85-9dc6-414f-a766-724e241eb4db", + "metadata": {}, + "outputs": [], + "source": [ + "# Benchmark Function\n", + "\n", + "def run_cnn_benchmark(augment_type=\"none\"):\n", + " print(f\"\\nRunning benchmark for: {augment_type}\")\n", + "\n", + " # Split file paths first to avoid augmenting validation/test data\n", + " train_files, temp_files, train_labels, temp_labels = train_test_split(\n", + " audio_files,\n", + " labels,\n", + " test_size=0.30,\n", + " random_state=SEED,\n", + " stratify=labels\n", + " )\n", + "\n", + " val_files, test_files, val_labels, test_labels = train_test_split(\n", + " temp_files,\n", + " temp_labels,\n", + " test_size=0.50,\n", + " random_state=SEED,\n", + " stratify=temp_labels\n", + " )\n", + "\n", + " label_encoder = LabelEncoder()\n", + " label_encoder.fit(labels)\n", + "\n", + " def build_features(file_list, label_list, use_augmentation=False):\n", + " X_data = []\n", + " y_data = []\n", + "\n", + " for file_path, label in zip(file_list, label_list):\n", + " try:\n", + " method = augment_type if use_augmentation else \"none\"\n", + " spec = extract_mel_spectrogram(file_path, method)\n", + "\n", + " X_data.append(spec)\n", + " y_data.append(label)\n", + "\n", + " except Exception as e:\n", + " print(\"Skipped:\", file_path, e)\n", + "\n", + " X_data = np.array(X_data)\n", + " X_data = X_data[..., np.newaxis]\n", + "\n", + " y_encoded = label_encoder.transform(y_data)\n", + " y_encoded = to_categorical(y_encoded, num_classes=len(label_encoder.classes_))\n", + "\n", + " return X_data, y_encoded\n", + "\n", + " # Augmentation only applied to training data\n", + " X_train, y_train = build_features(train_files, train_labels, use_augmentation=True)\n", + "\n", + " # Validation and test data stay clean\n", + " X_val, y_val = build_features(val_files, val_labels, use_augmentation=False)\n", + " X_test, y_test = build_features(test_files, test_labels, use_augmentation=False)\n", + "\n", + " model = build_cnn_model(\n", + " input_shape=X_train.shape[1:],\n", + " num_classes=len(label_encoder.classes_)\n", + " )\n", + "\n", + " history = model.fit(\n", + " X_train,\n", + " y_train,\n", + " validation_data=(X_val, y_val),\n", + " epochs=15,\n", + " batch_size=16,\n", + " verbose=1\n", + " )\n", + "\n", + " # Training curve\n", + " plt.figure()\n", + " plt.plot(history.history[\"accuracy\"], label=\"Training Accuracy\")\n", + " plt.plot(history.history[\"val_accuracy\"], label=\"Validation Accuracy\")\n", + " plt.title(f\"Training Curve - {augment_type}\")\n", + " plt.xlabel(\"Epoch\")\n", + " plt.ylabel(\"Accuracy\")\n", + " plt.legend()\n", + " plt.show()\n", + "\n", + " # Prediction\n", + " y_pred_prob = model.predict(X_test)\n", + " y_pred = np.argmax(y_pred_prob, axis=1)\n", + " y_true = np.argmax(y_test, axis=1)\n", + "\n", + " # Metrics\n", + " accuracy = accuracy_score(y_true, y_pred)\n", + " f1 = f1_score(y_true, y_pred, average=\"weighted\")\n", + "\n", + " # Confusion matrix\n", + " cm = confusion_matrix(y_true, y_pred)\n", + " disp = ConfusionMatrixDisplay(\n", + " confusion_matrix=cm,\n", + " display_labels=label_encoder.classes_\n", + " )\n", + " disp.plot(xticks_rotation=45)\n", + " plt.title(f\"Confusion Matrix - {augment_type}\")\n", + " plt.show()\n", + "\n", + " return accuracy, f1, y_true, y_pred, label_encoder, history" + ] + }, + { + "cell_type": "markdown", + "id": "7932889b-1319-4480-8dd9-f3869d747215", + "metadata": {}, + "source": [ + "### Running the Benchmark\n", + "\n", + "Each augmentation method is evaluated using the same dataset, model architecture, and training configuration to ensure a fair comparison.\n", + "\n", + "The benchmark is executed for all selected methods, including a combined augmentation approach. Accuracy and F1 score are recorded for each method to measure performance.\n", + "\n", + "The results are organised into a table to make it easy to compare methods and identify which augmentation techniques are most effective." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "cebad547-c4d6-406e-88c1-9cd7223b6983", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Running benchmark for: none\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\kiran\\anaconda3\\envs\\projectecho\\lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", + " from .autonotebook import tqdm as notebook_tqdm\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/15\n", + "9/9 [==============================] - 7s 640ms/step - loss: 18.7810 - accuracy: 0.2462 - val_loss: 5.5527 - val_accuracy: 0.2143\n", + "Epoch 2/15\n", + "9/9 [==============================] - 7s 805ms/step - loss: 4.1559 - accuracy: 0.4000 - val_loss: 6.6974 - val_accuracy: 0.2857\n", + "Epoch 3/15\n", + "9/9 [==============================] - 4s 500ms/step - loss: 1.6717 - accuracy: 0.5077 - val_loss: 5.3665 - val_accuracy: 0.2857\n", + "Epoch 4/15\n", + "9/9 [==============================] - 4s 479ms/step - loss: 1.1316 - accuracy: 0.5308 - val_loss: 1.9404 - val_accuracy: 0.3571\n", + "Epoch 5/15\n", + "9/9 [==============================] - 5s 538ms/step - loss: 1.0514 - accuracy: 0.6154 - val_loss: 2.6170 - val_accuracy: 0.2857\n", + "Epoch 6/15\n", + "9/9 [==============================] - 6s 633ms/step - loss: 1.1156 - accuracy: 0.6154 - val_loss: 2.4878 - val_accuracy: 0.2500\n", + "Epoch 7/15\n", + "9/9 [==============================] - 6s 648ms/step - loss: 1.0733 - accuracy: 0.5769 - val_loss: 1.5437 - val_accuracy: 0.2143\n", + "Epoch 8/15\n", + "9/9 [==============================] - 6s 714ms/step - loss: 0.9694 - accuracy: 0.5385 - val_loss: 1.6278 - val_accuracy: 0.3214\n", + "Epoch 9/15\n", + "9/9 [==============================] - 8s 825ms/step - loss: 1.0017 - accuracy: 0.5385 - val_loss: 1.7338 - val_accuracy: 0.4286\n", + "Epoch 10/15\n", + "9/9 [==============================] - 9s 1s/step - loss: 0.9437 - accuracy: 0.6077 - val_loss: 2.2668 - val_accuracy: 0.1786\n", + "Epoch 11/15\n", + "9/9 [==============================] - 6s 698ms/step - loss: 0.8879 - accuracy: 0.6538 - val_loss: 3.3788 - val_accuracy: 0.2857\n", + "Epoch 12/15\n", + "9/9 [==============================] - 6s 675ms/step - loss: 0.9713 - accuracy: 0.5308 - val_loss: 4.8823 - val_accuracy: 0.2143\n", + "Epoch 13/15\n", + "9/9 [==============================] - 7s 830ms/step - loss: 0.9035 - accuracy: 0.6077 - val_loss: 6.5644 - val_accuracy: 0.1429\n", + "Epoch 14/15\n", + "9/9 [==============================] - 8s 884ms/step - loss: 0.9024 - accuracy: 0.6923 - val_loss: 5.8581 - val_accuracy: 0.1429\n", + "Epoch 15/15\n", + "9/9 [==============================] - 8s 872ms/step - loss: 0.8738 - accuracy: 0.6846 - val_loss: 4.4005 - val_accuracy: 0.1786\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "none: Accuracy=0.286, F1=0.167\n", + "\n", + "Running benchmark for: time_stretch\n", + "Epoch 1/15\n", + "9/9 [==============================] - 5s 512ms/step - loss: 19.2204 - accuracy: 0.1923 - val_loss: 8.9528 - val_accuracy: 0.2143\n", + "Epoch 2/15\n", + "9/9 [==============================] - 3s 273ms/step - loss: 8.0674 - accuracy: 0.3769 - val_loss: 3.7880 - val_accuracy: 0.2500\n", + "Epoch 3/15\n", + "9/9 [==============================] - 3s 332ms/step - loss: 3.2576 - accuracy: 0.4769 - val_loss: 4.8679 - val_accuracy: 0.3571\n", + "Epoch 4/15\n", + "9/9 [==============================] - 4s 402ms/step - loss: 2.0821 - accuracy: 0.4615 - val_loss: 2.7288 - val_accuracy: 0.3571\n", + "Epoch 5/15\n", + "9/9 [==============================] - 4s 485ms/step - loss: 1.8914 - accuracy: 0.4385 - val_loss: 1.9323 - val_accuracy: 0.2500\n", + "Epoch 6/15\n", + "9/9 [==============================] - 5s 571ms/step - loss: 1.4278 - accuracy: 0.4615 - val_loss: 1.7721 - val_accuracy: 0.2857\n", + "Epoch 7/15\n", + "9/9 [==============================] - 6s 662ms/step - loss: 1.3172 - accuracy: 0.4923 - val_loss: 1.5460 - val_accuracy: 0.2500\n", + "Epoch 8/15\n", + "9/9 [==============================] - 8s 916ms/step - loss: 1.3499 - accuracy: 0.4154 - val_loss: 1.5371 - val_accuracy: 0.2857\n", + "Epoch 9/15\n", + "9/9 [==============================] - 7s 773ms/step - loss: 1.2868 - accuracy: 0.4308 - val_loss: 1.5202 - val_accuracy: 0.3929\n", + "Epoch 10/15\n", + "9/9 [==============================] - 7s 782ms/step - loss: 1.4310 - accuracy: 0.4538 - val_loss: 1.5295 - val_accuracy: 0.3571\n", + "Epoch 11/15\n", + "9/9 [==============================] - 4s 484ms/step - loss: 1.0948 - accuracy: 0.4923 - val_loss: 1.5829 - val_accuracy: 0.2143\n", + "Epoch 12/15\n", + "9/9 [==============================] - 4s 424ms/step - loss: 1.1272 - accuracy: 0.4308 - val_loss: 1.6692 - val_accuracy: 0.2500\n", + "Epoch 13/15\n", + "9/9 [==============================] - 5s 569ms/step - loss: 1.1082 - accuracy: 0.4615 - val_loss: 1.7102 - val_accuracy: 0.2857\n", + "Epoch 14/15\n", + "9/9 [==============================] - 6s 627ms/step - loss: 1.0589 - accuracy: 0.5000 - val_loss: 1.8072 - val_accuracy: 0.2500\n", + "Epoch 15/15\n", + "9/9 [==============================] - 6s 640ms/step - loss: 1.1988 - accuracy: 0.4923 - val_loss: 1.9815 - val_accuracy: 0.1429\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "time_stretch: Accuracy=0.143, F1=0.145\n", + "\n", + "Running benchmark for: pitch_shift\n", + "Epoch 1/15\n", + "9/9 [==============================] - 9s 872ms/step - loss: 16.4030 - accuracy: 0.2846 - val_loss: 9.6440 - val_accuracy: 0.2143\n", + "Epoch 2/15\n", + "9/9 [==============================] - 8s 848ms/step - loss: 6.5855 - accuracy: 0.3615 - val_loss: 15.6236 - val_accuracy: 0.2500\n", + "Epoch 3/15\n", + "9/9 [==============================] - 7s 728ms/step - loss: 3.1597 - accuracy: 0.4538 - val_loss: 1.6983 - val_accuracy: 0.1429\n", + "Epoch 4/15\n", + "9/9 [==============================] - 6s 584ms/step - loss: 2.0003 - accuracy: 0.3846 - val_loss: 1.9725 - val_accuracy: 0.1786\n", + "Epoch 5/15\n", + "9/9 [==============================] - 6s 708ms/step - loss: 1.9967 - accuracy: 0.3692 - val_loss: 1.6248 - val_accuracy: 0.2500\n", + "Epoch 6/15\n", + "9/9 [==============================] - 7s 826ms/step - loss: 1.3509 - accuracy: 0.4538 - val_loss: 1.4950 - val_accuracy: 0.3214\n", + "Epoch 7/15\n", + "9/9 [==============================] - 8s 849ms/step - loss: 1.2155 - accuracy: 0.5077 - val_loss: 1.5434 - val_accuracy: 0.2500\n", + "Epoch 8/15\n", + "9/9 [==============================] - 7s 810ms/step - loss: 1.4346 - accuracy: 0.3846 - val_loss: 1.5173 - val_accuracy: 0.2857\n", + "Epoch 9/15\n", + "9/9 [==============================] - 6s 685ms/step - loss: 1.1480 - accuracy: 0.5077 - val_loss: 1.5286 - val_accuracy: 0.2500\n", + "Epoch 10/15\n", + "9/9 [==============================] - 5s 537ms/step - loss: 1.1644 - accuracy: 0.5846 - val_loss: 1.5427 - val_accuracy: 0.2857\n", + "Epoch 11/15\n", + "9/9 [==============================] - 5s 543ms/step - loss: 1.2235 - accuracy: 0.5923 - val_loss: 1.5279 - val_accuracy: 0.2857\n", + "Epoch 12/15\n", + "9/9 [==============================] - 6s 669ms/step - loss: 1.0731 - accuracy: 0.5538 - val_loss: 1.6538 - val_accuracy: 0.2857\n", + "Epoch 13/15\n", + "9/9 [==============================] - 6s 709ms/step - loss: 1.0040 - accuracy: 0.6538 - val_loss: 1.9271 - val_accuracy: 0.3214\n", + "Epoch 14/15\n", + "9/9 [==============================] - 7s 756ms/step - loss: 1.0173 - accuracy: 0.5615 - val_loss: 2.4365 - val_accuracy: 0.2857\n", + "Epoch 15/15\n", + "9/9 [==============================] - 7s 754ms/step - loss: 0.9692 - accuracy: 0.6769 - val_loss: 2.3428 - val_accuracy: 0.2857\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "pitch_shift: Accuracy=0.286, F1=0.221\n", + "\n", + "Running benchmark for: noise\n", + "Epoch 1/15\n", + "9/9 [==============================] - 8s 839ms/step - loss: 15.3401 - accuracy: 0.2308 - val_loss: 5.0407 - val_accuracy: 0.2143\n", + "Epoch 2/15\n", + "9/9 [==============================] - 10s 1s/step - loss: 4.4093 - accuracy: 0.4462 - val_loss: 5.0534 - val_accuracy: 0.2143\n", + "Epoch 3/15\n", + "9/9 [==============================] - 8s 803ms/step - loss: 1.8144 - accuracy: 0.5385 - val_loss: 2.7458 - val_accuracy: 0.2500\n", + "Epoch 4/15\n", + "9/9 [==============================] - 8s 845ms/step - loss: 1.6656 - accuracy: 0.3231 - val_loss: 3.2031 - val_accuracy: 0.2500\n", + "Epoch 5/15\n", + "9/9 [==============================] - 9s 1s/step - loss: 1.1572 - accuracy: 0.5923 - val_loss: 3.3537 - val_accuracy: 0.2143\n", + "Epoch 6/15\n", + "9/9 [==============================] - 9s 1s/step - loss: 1.3975 - accuracy: 0.4462 - val_loss: 1.6308 - val_accuracy: 0.2857\n", + "Epoch 7/15\n", + "9/9 [==============================] - 10s 1s/step - loss: 1.1757 - accuracy: 0.4538 - val_loss: 1.5640 - val_accuracy: 0.2857\n", + "Epoch 8/15\n", + "9/9 [==============================] - 12s 1s/step - loss: 1.2287 - accuracy: 0.5077 - val_loss: 1.9549 - val_accuracy: 0.3214\n", + "Epoch 9/15\n", + "9/9 [==============================] - 8s 879ms/step - loss: 1.1959 - accuracy: 0.5077 - val_loss: 1.5339 - val_accuracy: 0.2143\n", + "Epoch 10/15\n", + "9/9 [==============================] - 7s 826ms/step - loss: 1.1697 - accuracy: 0.5000 - val_loss: 1.4848 - val_accuracy: 0.2857\n", + "Epoch 11/15\n", + "9/9 [==============================] - 7s 796ms/step - loss: 1.1521 - accuracy: 0.5154 - val_loss: 1.4048 - val_accuracy: 0.4286\n", + "Epoch 12/15\n", + "9/9 [==============================] - 8s 877ms/step - loss: 1.3101 - accuracy: 0.5154 - val_loss: 1.3992 - val_accuracy: 0.4286\n", + "Epoch 13/15\n", + "9/9 [==============================] - 7s 757ms/step - loss: 1.1041 - accuracy: 0.5231 - val_loss: 1.8133 - val_accuracy: 0.3214\n", + "Epoch 14/15\n", + "9/9 [==============================] - 6s 693ms/step - loss: 1.2883 - accuracy: 0.5462 - val_loss: 1.8277 - val_accuracy: 0.4643\n", + "Epoch 15/15\n", + "9/9 [==============================] - 6s 613ms/step - loss: 1.2097 - accuracy: 0.5385 - val_loss: 1.3749 - val_accuracy: 0.5000\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "noise: Accuracy=0.393, F1=0.328\n", + "\n", + "Running benchmark for: specaugment\n", + "Epoch 1/15\n", + "9/9 [==============================] - 7s 644ms/step - loss: 18.2277 - accuracy: 0.2308 - val_loss: 6.4039 - val_accuracy: 0.2143\n", + "Epoch 2/15\n", + "9/9 [==============================] - 6s 674ms/step - loss: 6.9361 - accuracy: 0.2846 - val_loss: 2.2761 - val_accuracy: 0.2500\n", + "Epoch 3/15\n", + "9/9 [==============================] - 5s 589ms/step - loss: 2.0354 - accuracy: 0.3231 - val_loss: 1.6575 - val_accuracy: 0.2500\n", + "Epoch 4/15\n", + "9/9 [==============================] - 6s 634ms/step - loss: 1.7167 - accuracy: 0.2462 - val_loss: 1.5575 - val_accuracy: 0.3214\n", + "Epoch 5/15\n", + "9/9 [==============================] - 5s 548ms/step - loss: 1.8151 - accuracy: 0.3231 - val_loss: 1.5076 - val_accuracy: 0.3214\n", + "Epoch 6/15\n", + "9/9 [==============================] - 5s 566ms/step - loss: 1.4767 - accuracy: 0.3308 - val_loss: 1.5498 - val_accuracy: 0.2857\n", + "Epoch 7/15\n", + "9/9 [==============================] - 5s 572ms/step - loss: 1.3710 - accuracy: 0.4000 - val_loss: 1.5938 - val_accuracy: 0.2500\n", + "Epoch 8/15\n", + "9/9 [==============================] - 5s 569ms/step - loss: 1.4458 - accuracy: 0.3846 - val_loss: 1.8795 - val_accuracy: 0.3214\n", + "Epoch 9/15\n", + "9/9 [==============================] - 5s 582ms/step - loss: 1.2966 - accuracy: 0.4077 - val_loss: 2.4011 - val_accuracy: 0.3214\n", + "Epoch 10/15\n", + "9/9 [==============================] - 5s 569ms/step - loss: 1.3641 - accuracy: 0.3692 - val_loss: 2.8288 - val_accuracy: 0.2500\n", + "Epoch 11/15\n", + "9/9 [==============================] - 5s 565ms/step - loss: 1.2836 - accuracy: 0.4000 - val_loss: 3.4222 - val_accuracy: 0.3214\n", + "Epoch 12/15\n", + "9/9 [==============================] - 5s 576ms/step - loss: 1.3743 - accuracy: 0.4538 - val_loss: 3.9592 - val_accuracy: 0.1429\n", + "Epoch 13/15\n", + "9/9 [==============================] - 5s 577ms/step - loss: 1.3188 - accuracy: 0.4615 - val_loss: 6.1713 - val_accuracy: 0.2857\n", + "Epoch 14/15\n", + "9/9 [==============================] - 5s 584ms/step - loss: 1.2739 - accuracy: 0.4692 - val_loss: 8.9721 - val_accuracy: 0.2143\n", + "Epoch 15/15\n", + "9/9 [==============================] - 5s 570ms/step - loss: 1.3374 - accuracy: 0.4462 - val_loss: 10.3791 - val_accuracy: 0.1786\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:5 out of the last 5 calls to .predict_function at 0x00000260069D3790> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n", + "1/1 [==============================] - 0s 426ms/step\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "specaugment: Accuracy=0.179, F1=0.077\n", + "\n", + "Running benchmark for: noise_specaugment\n", + "Epoch 1/15\n", + "9/9 [==============================] - 4s 369ms/step - loss: 13.4133 - accuracy: 0.2769 - val_loss: 4.5821 - val_accuracy: 0.2500\n", + "Epoch 2/15\n", + "9/9 [==============================] - 5s 580ms/step - loss: 7.5768 - accuracy: 0.3846 - val_loss: 3.0095 - val_accuracy: 0.1429\n", + "Epoch 3/15\n", + "9/9 [==============================] - 5s 600ms/step - loss: 2.7970 - accuracy: 0.5615 - val_loss: 2.1440 - val_accuracy: 0.2143\n", + "Epoch 4/15\n", + "9/9 [==============================] - 5s 592ms/step - loss: 2.0190 - accuracy: 0.5000 - val_loss: 1.5920 - val_accuracy: 0.2143\n", + "Epoch 5/15\n", + "9/9 [==============================] - 5s 601ms/step - loss: 1.4963 - accuracy: 0.4538 - val_loss: 1.7494 - val_accuracy: 0.2143\n", + "Epoch 6/15\n", + "9/9 [==============================] - 5s 578ms/step - loss: 1.3026 - accuracy: 0.5385 - val_loss: 2.1072 - val_accuracy: 0.2143\n", + "Epoch 7/15\n", + "9/9 [==============================] - 5s 586ms/step - loss: 1.1260 - accuracy: 0.5538 - val_loss: 2.4662 - val_accuracy: 0.2500\n", + "Epoch 8/15\n", + "9/9 [==============================] - 6s 622ms/step - loss: 1.0125 - accuracy: 0.6462 - val_loss: 3.2706 - val_accuracy: 0.2500\n", + "Epoch 9/15\n", + "9/9 [==============================] - 6s 628ms/step - loss: 1.0951 - accuracy: 0.5846 - val_loss: 2.0057 - val_accuracy: 0.2857\n", + "Epoch 10/15\n", + "9/9 [==============================] - 6s 638ms/step - loss: 1.0071 - accuracy: 0.5769 - val_loss: 1.5576 - val_accuracy: 0.2500\n", + "Epoch 11/15\n", + "9/9 [==============================] - 6s 671ms/step - loss: 1.0177 - accuracy: 0.5077 - val_loss: 1.6530 - val_accuracy: 0.2857\n", + "Epoch 12/15\n", + "9/9 [==============================] - 5s 586ms/step - loss: 1.0308 - accuracy: 0.5231 - val_loss: 1.8830 - val_accuracy: 0.3214\n", + "Epoch 13/15\n", + "9/9 [==============================] - 6s 683ms/step - loss: 1.0022 - accuracy: 0.5692 - val_loss: 2.8061 - val_accuracy: 0.3214\n", + "Epoch 14/15\n", + "9/9 [==============================] - 6s 667ms/step - loss: 1.1456 - accuracy: 0.6154 - val_loss: 2.1473 - val_accuracy: 0.2500\n", + "Epoch 15/15\n", + "9/9 [==============================] - 5s 591ms/step - loss: 0.9428 - accuracy: 0.6154 - val_loss: 3.1016 - val_accuracy: 0.3214\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "WARNING:tensorflow:6 out of the last 6 calls to .predict_function at 0x0000026004372F70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n", + "1/1 [==============================] - 0s 358ms/step\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "noise_specaugment: Accuracy=0.214, F1=0.129\n" + ] + } + ], + "source": [ + "# Run Benchmark\n", + "\n", + "methods = [\n", + " \"none\",\n", + " \"time_stretch\",\n", + " \"pitch_shift\",\n", + " \"noise\",\n", + " \"specaugment\",\n", + " \"noise_specaugment\"\n", + "]\n", + "\n", + "results = []\n", + "saved_outputs = {}\n", + "\n", + "for method in methods:\n", + " acc, f1, y_true, y_pred, label_encoder, history = run_cnn_benchmark(method)\n", + "\n", + " results.append([method, acc, f1])\n", + "\n", + " saved_outputs[method] = {\n", + " \"y_true\": y_true,\n", + " \"y_pred\": y_pred,\n", + " \"label_encoder\": label_encoder,\n", + " \"history\": history\n", + " }\n", + "\n", + " print(f\"{method}: Accuracy={acc:.3f}, F1={f1:.3f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "c50f8576-7b3e-4f14-a14c-f9e69a4ab77c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " Benchmark Results Summary\n" + ] + }, + { + "data": { + "text/html": [ + "
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MethodAccuracyF1 Score
0noise0.3930.328
1none0.2860.167
2pitch_shift0.2860.221
3noise_specaugment0.2140.129
4specaugment0.1790.077
5time_stretch0.1430.145
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" + ], + "text/plain": [ + " Method Accuracy F1 Score\n", + "0 noise 0.393 0.328\n", + "1 none 0.286 0.167\n", + "2 pitch_shift 0.286 0.221\n", + "3 noise_specaugment 0.214 0.129\n", + "4 specaugment 0.179 0.077\n", + "5 time_stretch 0.143 0.145" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Results Table\n", + "\n", + "results_df = pd.DataFrame(\n", + " results,\n", + " columns=[\"Method\", \"Accuracy\", \"F1 Score\"]\n", + ")\n", + "\n", + "results_df = results_df.sort_values(by=\"Accuracy\", ascending=False)\n", + "results_df = results_df.round(3)\n", + "results_df = results_df.reset_index(drop=True)\n", + "\n", + "print(\"\\n Benchmark Results Summary\")\n", + "display(results_df)" + ] + }, + { + "cell_type": "markdown", + "id": "84ec361c-00a4-4de3-be4d-0b939a282a59", + "metadata": {}, + "source": [ + "### Results Summary\n", + "\n", + "The results show that different augmentation methods have varying effects on model performance.\n", + "\n", + "Noise injection achieved the highest accuracy (0.393) and F1 score (0.328), showing a clear improvement over the baseline model. This suggests that adding noise helped the model generalise better.\n", + "\n", + "The baseline and pitch shifting produced similar accuracy results, although pitch shifting slightly improved the F1 score. This indicates a minor benefit.\n", + "\n", + "SpecAugment, time stretching, and the combined method (noise + SpecAugment) performed worse than the baseline. This may be due to excessive distortion or loss of important audio features.\n", + "\n", + "Overall, noise injection was the most effective method in this benchmark." + ] + }, + { + "cell_type": "markdown", + "id": "7a2ddef3-cda2-4483-bd89-25e0814916a3", + "metadata": {}, + "source": [ + "### Final Recommendations\n", + "\n", + "| Method | Accuracy | F1 Score | Decision |\n", + "|--------|---------:|---------:|----------|\n", + "| Noise | 0.393 | 0.328 | Keep |\n", + "| Pitch Shift | 0.286 | 0.221 | Defer |\n", + "| Noise + SpecAugment | 0.214 | 0.129 | Defer |\n", + "| SpecAugment | 0.179 | 0.077 | Drop |\n", + "| Time Stretch | 0.143 | 0.145 | Drop |\n", + "| None (baseline) | 0.286 | 0.167 | Reference only |" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "29e7e057-ac01-49ea-83b2-2a9999d00422", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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EjLKSKsSqTIcGZ+jHUwNkMqKATAMAFITEXmAk6njfHwoElCVXQHf77be7oEY/6Mr6KDiLPV6DmaKs2J97cqDvWwML4gV/ygi+/vrrLqseGwCLLmg08CW7ApiMzpHx9vm1115rTzzxhMtaN2vWzAXl2k4N/jiQc4xaTu655x4X3CljqfeuQTuxmW3x+1LBJLIegR2yhH6s9aPtR+QFKZOjkazjx493JyB/FR07OjE2G6GRfBJvpGZm18fTj5XoPWQ0Mm5/ZXSy10lPGUz9eOlHzPNZw31ZRzzaX/qhjOWbyvz+zGzK5GhUpUYqTpkyZY/7WE2kxx9//F5//P/tD6V/r9ofwcybmmeVUfafsV9O+17Z2mDTlZZTE1WQmjjVvUA3rUtlTPTDPmDAgDRNp0Fnn322K3GizI+W29ftDm6PfywrPkO992DtNmVPdZGmsh5+FLWa8fQ91uhNT/vn39rT/lSgr6xYRse0skiZFSgr+NY5TJmsYKCi96yg7uGHH04XpGi7br31VpdlVPcHHd8zZsxw2fiMsnZaRkGVukXogi4jOkfGnh+1f/S57CuNTu/SpYvdd9990cf0XmLXq21Ss+reKKt39NFHu/2kjLBGY2tUczw6NnyGEFmPplhkOqX8dQLU1Zua4WJv11xzjWuKeu2119zy+nHSlbVKBgTpaj1IzRo6mTz99NPux8bT0H71vctMrVq1chmJu+66y/2oxzqQKXL0oySxJ1KfVYjNIqgMSLwfvnjriEc/xCoKPXv27DQ1rVTKQ2UMMrv5x1O2UT98Ks+gIGZPWUplHFQmI16tt+B71Pv+N9X9FbipOVBFgIP7WcWA9eOtPmui8hr68dFFh344g2UkYv9+sBSNaP3ap1p/vGPG03dAfUIVsAQ/G0/fDZVC8dujiwttj0q6BPt5aeYDv92ZScdHcPv1WerzUPY1o+NV+yr2+7q/9rY/9XeV5VfZjGCzsLp2KFukYErf2cygjJb+rsq0BCkY14WB+mDGntdU3kjHvs9Aq36b1hEv2+j3nfoLKiBV5jM2axbcvwq2Ys+P+pz2p1VD+y/2HKNALHYd2m71F9TFd0bb7V166aWua4rOVcpy+mMklvaj9imyBxk7ZDoFbPpxOuecc+I+r0EBvlixrsx1Rax+GTrJKDOjk5iaY+L1sVKgpZpzyvKoQ7ayXWPHjnUBXzDY+7f0A6EfNJ24GjZs6JortM26KlWHdf19/d39oayUfqiUxTr88MPdVby2WzdlPkaOHOl+wNQnSSfLeBkQDSwQ/fBrm9T3S8GTD/iCbr75ZpcZ0sn2uuuuc3/vqaeecutVM1dsZ+3MpMzA3qg5T5k91bxasGCB+9HW+1HGSAMrVP/L98/T+9bncccdd7j+lAp2YjNYe6LPTlkf/ciqeVvHpjIsCkaOOeaYaP8w/X39DW2X1q/jU/tLTVixfey0vWqm17GgvpEKtHRMKNja0+AI/Q1d+CjY1OeuAFfr0OPqu6YgRRkaBX56TLNS6FjX/lKTlwIZ7RsF56o1ltkUpKk2nLbL7yMFTf77fNxxx7nt02es40rfWXVZ+LfN3vuyP/XZaGCTtkcDStQlQrMaKOjV9yezaP0KVJRR9seZBm9pQI/eczzqt6YLQh27fhYRnT/0bx3TvluFaiLqOV3g6ljWd1kXNxrYoQyl1qMBJLqQ9fXgNCBGwaSCLg02UuClbOD+NG3qQlufk863Og/pokLvT+8zSN1BlN3TOVm1NPXdU9ZR53VdYASz1up20b9/fxcEapBNvALpOo9rUIX6TCKbZMFIW+RwZ599tqunFayNFK++00EHHRRZv359tBSIar+pXIJqK6l0gmpWxZY7EZVtUE0z1a5SGYjXXnvNvVaPxZY7UXmQIF/aQzWdMirZEbt8q1atXHkKvSfVrtK2q5SLp3IDqq0Vy9dNC/rss89cOQmVbAiWMFi5cqUreaASK/pbKhOiMg7xyhyoplSlSpVcmYRg6ZPY0geishCqC6b1avtVl06lMvZln8QrNxNPRvsuVrw6dr6UiPaJynKobIVK2vTv39+9/2CZGb1WzwfLjuzpc4tXQkflTXSc6NhTHa5evXqlqQXnqf6gr4/WuHFjV3ImtjyHaq2pxIZKX2g5HRuqE5dR7bNY+rsqLaH3q+Nen4+OZ5Xk+e2339IsO2XKFFcmRX+nZMmSro6YjpmgjI5DbXO8MiKxn4fflx9++GGkZ8+e7nuo+mz6W7///nua13766aeuHqQ+M9XH0+flS2AE93lGf9s/dyD7c/78+e47qW3TflM5HX2vgvb3uIhHZUpq1qwZvX/fffe5186cOTPD1zz55JNpSsOo5IjOQTrm9J1X+SXVtJs3b16a16ncjv98td+1X3yZKFEpFNW1Uy04vWe9/8WLF2dY7iTed1HHm2p1ah3ad1qHyt7EO2/o81adR51ntN0qMaVl/Pk66Mwzz3R/M/Yz8FQHT9u8adOmDPcbMlcu/Se7gkggq6h/irIywVkPAOw7NTcrM6hskZqAczqVglFfOzV7K4OJjPvUqitMRv2c1Q9PM4zcf//92b5tORV97JBS1FQZOxepOnOraSInTJwOIHuo6b179+42YsSIRG9K0tLgDXVNUZNzPBrdrGbovQ0SQuaijx1SigoIq2+S+kSpD4pGw6nfh/rmxBYIBoB/Q/06kZ76nWr072OPPeb61alPajzqV5iZfZ+xbwjskFLUaVudeXVC0chUDRpQ52pdVcd2AgYAZD5VIlCzvQpAa0BWvFqfSBz62AEAAIQEfewAAABCgsAOAAAgJOhjF4eKSKoYpYpiMmkxAABIJPWaU+F/DRrcW3F5Ars4FNRl9uTcAAAA/8aKFSvc3Lx7QmAXh5++Rjsws+YeBAAAOBCbNm1yCac9TVfoEdjF4ZtfFdQR2AEAgGSwL93DGDwBAAAQEgR2AAAAIZEUgd24ceOsatWqVqBAAWvatKnNnTt3n143efJkl5Zs165dutEjgwYNsgoVKljBggXdFFSarw4AACDMEh7YTZkyxfr27WuDBw+2+fPnW/369a1Vq1a2du3aPb5u2bJl1q9fPzvhhBPSPTdy5EgbM2aMm0N0zpw5btoprXPbtm1Z+E4AAAByeGA3atQo69Gjh5t3rnbt2i4YK1SokE2cODHD1+zatcsuvvhiGzp0qFWvXj1dtm706NF26623Wtu2ba1evXr29NNPuxIm06ZNy4Z3BAAAkAMDux07dti8efNcU2l0g3Lndvdnz56d4etuv/12K1u2rHXv3j3dc0uXLrXVq1enWWexYsVcE++e1gkAAJDqElruZP369S77Vq5cuTSP6/6iRYvivuaTTz6xxx9/3BYsWBD3eQV1fh2x6/TPxdq+fbu7BevFAAAApJqEN8XuD02ncemll9qECROsdOnSmbbe4cOHu6yevzHrBAAASEUJzdgpOMuTJ4+tWbMmzeO6X758+XTLL1myxA2aOPvss9PM6yp58+a1H3/8Mfo6rUOjYoPrbNCgQdztGDBggBvAEVvhGQAAIJUkNGOXL18+a9Sokc2cOTNNoKb7zZo1S7d8rVq17JtvvnHNsP52zjnn2CmnnOL+rWCsWrVqLrgLrlOBmkbHxlun5M+fPzrLBLNNAACAVJXwKcWUKevSpYs1btzYmjRp4ka0btmyxY2Slc6dO1ulSpVcc6nq3NWpUyfN64sXL+7+H3y8T58+dscdd9hhhx3mAr3bbrvNKlasmK7eHQAAQJgkPLDr0KGDrVu3zhUU1uAGNZdOnz49Ovhh+fLlbqTs/ujfv78LDnv27GkbNmyw5s2bu3UqMAQAAAirXBEVfkMaarrVIIqNGzdmabNs1ZvfzLJ1p6plI9okehMAAEjZuCSlRsUCAAAgYwR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBJJEdiNGzfOqlatagUKFLCmTZva3LlzM1x26tSp1rhxYytevLgVLlzYGjRoYM8880yaZbp27Wq5cuVKczvjjDOy4Z0AAAAkTl5LsClTpljfvn1t/PjxLqgbPXq0tWrVyn788UcrW7ZsuuVLlixpt9xyi9WqVcvy5ctnb7zxhnXr1s0tq9d5CuSeeOKJ6P38+fNn23sCAADIkRm7UaNGWY8ePVxwVrt2bRfgFSpUyCZOnBh3+ZNPPtnOPfdcO/LII61GjRrWu3dvq1evnn3yySdpllMgV758+eitRIkS2fSOAAAAcmBgt2PHDps3b561aNHifxuUO7e7P3v27L2+PhKJ2MyZM11278QTT0zz3KxZs1wW74gjjrBevXrZ77//nuF6tm/fbps2bUpzAwAASDUJbYpdv3697dq1y8qVK5fmcd1ftGhRhq/buHGjVapUyQVkefLksYceeshOP/30NM2w5513nlWrVs2WLFliAwcOtNatW7tgUcvHGj58uA0dOjST3x0AAEAO62N3IIoUKWILFiywzZs3u4yd+uhVr17dNdNKx44do8vWrVvXNdWq2VZZvNNOOy3d+gYMGODW4SljV7ly5Wx6NwAAACEI7EqXLu0yaGvWrEnzuO6rX1xG1Fxbs2ZN92+Niv3hhx9c1s0HdrEU9OlvLV68OG5gp/54DK4AAACpLqF97DSqtVGjRi7r5u3evdvdb9as2T6vR69Rs2xGVq5c6frYVahQ4V9vMwAAQLJKeFOsmkC7dOniatM1adLElTvZsmWLGyUrnTt3dv3plJET/V/LqmlVwdxbb73l6tg9/PDD7nk1z6q/XPv27V3WT33s+vfv7zJ8wXIoAAAAYZPwwK5Dhw62bt06GzRokK1evdo1rU6fPj06oGL58uWu6dVT0HfVVVe5LFzBggVdPbtnn33WrUfUtLtw4UJ76qmnbMOGDVaxYkVr2bKlDRs2jOZWAAAQarkiqhmCNDR4olixYm70bdGiRbPs71S9+c0sW3eqWjaiTaI3AQCAlI1LEl6gGAAAAJmDwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkkiKwGzdunFWtWtUKFChgTZs2tblz52a47NSpU61x48ZWvHhxK1y4sDVo0MCeeeaZNMtEIhEbNGiQVahQwQoWLGgtWrSwn376KRveCQAAQA4O7KZMmWJ9+/a1wYMH2/z5861+/frWqlUrW7t2bdzlS5YsabfccovNnj3bFi5caN26dXO3GTNmRJcZOXKkjRkzxsaPH29z5sxxAaDWuW3btmx8ZwAAANkrV0TprQRShu6YY46xsWPHuvu7d++2ypUr27XXXms333zzPq2jYcOG1qZNGxs2bJjL1lWsWNFuuOEG69evn3t+48aNVq5cOXvyySetY8eOe13fpk2brFixYu51RYsWtaxS9eY3s2zdqWrZiDaJ3gQAAJLK/sQlCc3Y7dixw+bNm+eaSqMblDu3u6+M3N4oiJs5c6b9+OOPduKJJ7rHli5daqtXr06zTu0MBZD7sk4AAIBUlTeRf3z9+vW2a9cul00L0v1FixZl+DpFrJUqVbLt27dbnjx57KGHHrLTTz/dPaegzq8jdp3+uVhaj27ByBgAACDVJDSwO1BFihSxBQsW2ObNm13GTn30qlevbieffPIBrW/48OE2dOjQTN9OAACA7JTQptjSpUu7jNuaNWvSPK775cuXz/B1aq6tWbOmGxGrvnTnn3++C87Ev25/1jlgwACXBfS3FStWZMK7AwAAyEGBXb58+axRo0Yu6+Zp8ITuN2vWbJ/Xo9f4ptRq1aq5AC64TjWtanRsRuvMnz+/64wYvAEAAKSahDfFqhm1S5curjZdkyZNbPTo0bZlyxZXwkQ6d+7s+tP5jJz+r2Vr1Kjhgrm33nrL1bF7+OGH3fO5cuWyPn362B133GGHHXaYC/Ruu+02N1K2Xbt2CX2vAAAAoQ7sOnToYOvWrXMFhTW4Qc2r06dPjw5+WL58uWt69RT0XXXVVbZy5UpXfLhWrVr27LPPuvV4/fv3d8v17NnTNmzYYM2bN3frVAFkAACAsEp4HbtkRB27xKGOHQAAKVrHDgAAAJmHwA4AACAkCOwAAABCgsAOAAAgJBI+KhbIbAxKyZpBKezX9BjsAyDZkLEDAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkCCwAwAACImkCOzGjRtnVatWtQIFCljTpk1t7ty5GS47YcIEO+GEE6xEiRLu1qJFi3TLd+3a1XLlypXmdsYZZ2TDOwEAAMjBgd2UKVOsb9++NnjwYJs/f77Vr1/fWrVqZWvXro27/KxZs6xTp072wQcf2OzZs61y5crWsmVL+/XXX9Msp0Dut99+i96ef/75bHpHAAAAOTSwGzVqlPXo0cO6detmtWvXtvHjx1uhQoVs4sSJcZd/7rnn7KqrrrIGDRpYrVq17LHHHrPdu3fbzJkz0yyXP39+K1++fPSm7B4AAECYJTSw27Fjh82bN881p0Y3KHdud1/ZuH2xdetW27lzp5UsWTJdZq9s2bJ2xBFHWK9evez333/P9O0HAABIJnkT+cfXr19vu3btsnLlyqV5XPcXLVq0T+u46aabrGLFimmCQzXDnnfeeVatWjVbsmSJDRw40Fq3bu2CxTx58qRbx/bt293N27Rp0796XwAAADkusPu3RowYYZMnT3bZOQ288Dp27Bj9d926da1evXpWo0YNt9xpp52Wbj3Dhw+3oUOHZtt2AwAAhK4ptnTp0i6DtmbNmjSP6776xe3Jvffe6wK7d955xwVue1K9enX3txYvXhz3+QEDBtjGjRujtxUrVhzAuwEAAMjBgV2+fPmsUaNGaQY++IEQzZo1y/B1I0eOtGHDhtn06dOtcePGe/07K1eudH3sKlSoEPd5DbQoWrRomhsAAEDoAzvVm7v99ttt+fLlmbIBKnWi2nRPPfWU/fDDD26gw5YtW9woWencubPLqHl333233XbbbW7UrLZl9erV7rZ582b3vP5/44032ueff27Lli1zQWLbtm2tZs2arowKAABAWO13YNenTx+bOnWqa948/fTTXR+34MCD/dWhQwfXrDpo0CBXwmTBggUuE+cHVCiAVB067+GHH3ajac8//3yXgfM3rUPUtLtw4UI755xz7PDDD7fu3bu7rODHH3/sMnMAAABhlSsSiUQO5IUqJvzkk0+6wr8a2XrRRRfZZZddZg0bNrRUp1GxxYoVc/3tsrJZturNb2bZulPVshFt/vU62K/psV+Td78CQGbGJQfcx04B3JgxY2zVqlVu1ggVCj7mmGNc1k3NpAcYLwIAACC7y52oKPArr7xiTzzxhL377rt27LHHumZPDVRQ3bj33nvPJk2adKCrBwAAQFYHdmqCVTCnJljNEqHBDffff7+b3ss799xzXfYOAAAASRzYKWDToAkNYmjXrp0ddNBB6ZbRjA/BIsEAAABIwsDu559/tipVquxxmcKFC7usHgAAALLPfg+eWLt2rc2ZMyfd43rsyy+/zKztAgAAQFYHdldffXXcKbd+/fVX9xwAAABSJLD7/vvv49aqO/roo91zAAAASJHATrM3rFmzJt3jmh0ib94Drp4CAACA7A7sWrZs6eZuVfVjb8OGDa52nUbLAgAAIDH2O8WmOVlPPPFENzJWza+i+V01t+szzzyTFdsIAACArAjsKlWqZAsXLrTnnnvOvv76aytYsKB169bNOnXqFLemHQAAALLHAXWKU526nj17Zv7WAAAA4IAd8GgHjYBdvny57dixI83j55xzzoFvDQAAALJ35gnNBfvNN99Yrly5LBKJuMf1b9m1a9eBbw0AAACyb1Rs79693VywmoGiUKFC9t1339lHH31kjRs3tlmzZh34lgAAACB7M3azZ8+2999/30qXLm25c+d2t+bNm9vw4cPtuuuus6+++urfbREAAACyJ2OnptYiRYq4fyu4W7Vqlfu3yp/8+OOPB7YVAAAAyP6MXZ06dVyZEzXHNm3a1EaOHGn58uWzRx991KpXr/7vtwgAAADZE9jdeuuttmXLFvfv22+/3c466yw74YQTrFSpUjZlypQD2woAAABkf2DXqlWr6L9r1qxpixYtsj/++MNKlCgRHRkLAACAJA/sdu7c6Waa0BRiapL1SpYsmRXbBgA5QtWb30z0JiSdZSPaJHoTgPAPntCUYYceeii16gAAAMIwKvaWW26xgQMHuuZXAAAApHAfu7Fjx9rixYutYsWKrsSJ5o0Nmj9/fmZuHwAAALIqsGvXrt3+vgQAAADJGNgNHjw4a7YEAAAA2dvHLiuMGzfOqlatagUKFHBFj+fOnZvhshMmTHB181ReRbcWLVqkWz4SidigQYOsQoUKbhSvlvnpp5+y4Z0AAACkUGCnuWHz5MmT4W1/qahx3759XSZQ/fPq16/vauWtXbs27vKzZs2yTp062QcffODmra1cubK1bNnSfv311+gymg1jzJgxNn78eJszZ47rB6h1btu2bb+3DwAAILRNsa+88kq62nZfffWVPfXUUzZ06ND93oBRo0ZZjx49rFu3bu6+grE333zTJk6caDfffHO65Z977rk09x977DF7+eWXbebMmda5c2eXrRs9erSbIaNt27ZumaefftrKlStn06ZNs44dO+73NgIAAIQysPPBUtD5559vRx11lMu+de/efZ/XtWPHDps3b54NGDAgTUZQTafKxu2LrVu3uuDSF0leunSprV692q3DK1asmGvi1TrjBXbbt293N2/Tpk37/B4AAABC18fu2GOPdVmz/bF+/XpX7FjZtCDdV3C2L2666SZXesUHcv51+7PO4cOHu+DP39S8CwAAkCMDu7///tv1aatUqZJlpxEjRtjkyZNd87AGXhwoZQw3btwYva1YsSJTtxMAACApm2I1EjVXrlzR++rT9tdff1mhQoXs2Wef3a91lS5d2g24WLNmTZrHdb98+fJ7fO29997rArv33nvP6tWrF33cv07r0KjY4DobNGgQd1358+d3NwAAgBwV2N1///1pAjv1iStTpozrw6agb3/ky5fPGjVq5JpwfeHj3bt3u/vXXHNNhq/TqNc777zTZsyYYY0bN07zXLVq1Vxwp3X4QE595jQ6tlevXvv5bgEAAEIc2HXt2jVTN0ClTrp06eICtCZNmrgRrVu2bImOktVIVzXxqh+c3H333a5G3aRJk1ztO99v7uCDD3Y3BZ19+vSxO+64ww477DAX6N12222uHx6zZgAAgDDb78DuiSeecAHUBRdckObxF1980Y1QVZC2Pzp06GDr1q1zwZqCNGXZpk+fHh38sHz5cpcV9B5++GE3mlYjcYNUB2/IkCHu3/3793fBYc+ePW3Dhg3WvHlzt85/0w8PAAAgdIGdMmePPPJIusfLli3rAqn9DexEza4ZNb2qIHHQsmXL9ro+Ze1uv/12dwMAAMgp9ntUrDJoat6MVaVKFfccAAAAUiSwU2Zu4cKF6R7/+uuvrVSpUpm1XQAAAMjqwE7ztF533XVurlYVF9bt/ffft969ezNdFwAAQCr1sRs2bJjr53baaadZ3rx5oyVKNHr1rrvuyoptBAAAQFYEdqo9pzlhVU5kwYIFVrBgQatbt67rYwcAAIAUCuw81YjTDQAAACnax659+/auSHC82SBia9sBAAAgiQO7jz76yM4888x0j7du3do9BwAAgBQJ7DZv3uz62cU66KCD3JysAAAASJE+dhooocETmgIsaPLkyVa7du3M3DYAAA5Y1ZvfTPQmJJ1lI9okehOQbIHdbbfdZuedd54tWbLETj31VPfYzJkzbdKkSfbSSy9lxTYCAAAgKwK7s88+26ZNm+Zq1imQU7mT+vXruyLFJUuW3N/VAQAAIJHlTtq0aeNuon51zz//vPXr18/mzZvnZqIAAABACgye8DQCtkuXLlaxYkW77777XLPs559/nrlbBwAAgKzJ2K1evdqefPJJe/zxx12m7sILL7Tt27e7plkGTgAAAKRIxk5964444ghbuHChjR492latWmUPPvhg1m4dAAAAMj9j9/bbb9t1111nvXr1YioxAACAVM7YffLJJ/bXX39Zo0aNrGnTpjZ27Fhbv3591m4dAAAAMj+wO/bYY23ChAn222+/2RVXXOEKEmvgxO7du+3dd991QR8AAABSaFRs4cKF7bLLLnMZvG+++cZuuOEGGzFihJUtW9bOOeecrNlKAAAAZF25E9FgipEjR9rKlStdLTsAAACkaGDn5cmTx9q1a2evvfZaZqwOAAAAiQrsAAAAkHgEdgAAACFBYAcAABASBHYAAAAhkfDAbty4cVa1alUrUKCAK3w8d+7cDJf97rvvrH379m75XLlyuanNYg0ZMsQ9F7zVqlUri98FAABADg/spkyZYn379rXBgwfb/PnzrX79+taqVStbu3Zt3OW3bt1q1atXd3Xzypcvn+F6jzrqKFdI2d9Ucw8AACDsEhrYjRo1ynr06GHdunWz2rVr2/jx461QoUI2ceLEuMsfc8wxds8991jHjh0tf/78Ga43b968LvDzt9KlS2fhuwAAAMjhgd2OHTts3rx51qJFi/9tTO7c7v7s2bP/1bp/+uknN92ZsnsXX3yxLV++PBO2GAAAILklLLBbv3697dq1y8qVK5fmcd1fvXr1Aa9X/fSefPJJmz59uj388MO2dOlSO+GEE/Y4l+327dtt06ZNaW4AAACpJq+FTOvWraP/rlevngv0qlSpYi+88IJ179497muGDx9uQ4cOzcatBAAACFHGTv3eNBXZmjVr0jyu+3saGLG/ihcvbocffrgtXrw4w2UGDBhgGzdujN5WrFiRaX8fAAAg9IFdvnz5rFGjRjZz5szoY7t373b3mzVrlml/Z/PmzbZkyRKrUKFChstoIEbRokXT3AAAAFJNQptiVeqkS5cu1rhxY2vSpImrS7dlyxY3SlY6d+5slSpVck2lfsDF999/H/33r7/+agsWLLCDDz7Yatas6R7v16+fnX322a75ddWqVa6UijKDnTp1SuA7BQAACHlg16FDB1u3bp0NGjTIDZho0KCBG/TgB1RoNKtGynoK1I4++ujo/XvvvdfdTjrpJJs1a5Z7bOXKlS6I+/33361MmTLWvHlz+/zzz92/AQAAwizhgyeuueYad4vHB2ueZpyIRCJ7XN/kyZMzdfsAAMD/VL35zURvQtJZNqKNJYuETykGAACAzEFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIJD+zGjRtnVatWtQIFCljTpk1t7ty5GS773XffWfv27d3yuXLlstGjR//rdQIAAIRFQgO7KVOmWN++fW3w4ME2f/58q1+/vrVq1crWrl0bd/mtW7da9erVbcSIEVa+fPlMWScAAEBYJDSwGzVqlPXo0cO6detmtWvXtvHjx1uhQoVs4sSJcZc/5phj7J577rGOHTta/vz5M2WdAAAAYZGwwG7Hjh02b948a9Gixf82Jndud3/27NlJs04AAIBUkTdRf3j9+vW2a9cuK1euXJrHdX/RokXZus7t27e7m7dp06YD+vsAAAA5evBEMhg+fLgVK1YseqtcuXKiNwkAACB1ArvSpUtbnjx5bM2aNWke1/2MBkZk1ToHDBhgGzdujN5WrFhxQH8fAAAgRwZ2+fLls0aNGtnMmTOjj+3evdvdb9asWbauUwMxihYtmuYGAACQahLWx05UlqRLly7WuHFja9KkiatLt2XLFjeiVTp37myVKlVyTaV+cMT3338f/fevv/5qCxYssIMPPthq1qy5T+sEAAAIq4QGdh06dLB169bZoEGDbPXq1dagQQObPn16dPDD8uXL3ahWb9WqVXb00UdH7997773udtJJJ9msWbP2aZ0AAABhldDATq655hp3i8cHa55mk4hEIv9qnQAAAGHFqFgAAICQILADAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkCCwAwAACAkCOwAAgJAgsAMAAAgJAjsAAICQILADAAAICQI7AACAkEiKwG7cuHFWtWpVK1CggDVt2tTmzp27x+VffPFFq1Wrllu+bt269tZbb6V5vmvXrpYrV640tzPOOCOL3wUAAEAOD+ymTJliffv2tcGDB9v8+fOtfv361qpVK1u7dm3c5T/77DPr1KmTde/e3b766itr166du3377bdpllMg99tvv0Vvzz//fDa9IwAAgBwa2I0aNcp69Ohh3bp1s9q1a9v48eOtUKFCNnHixLjLP/DAAy5ou/HGG+3II4+0YcOGWcOGDW3s2LFplsufP7+VL18+eitRokQ2vSMAAIAcGNjt2LHD5s2bZy1atPjfBuXO7e7Pnj077mv0eHB5UYYvdvlZs2ZZ2bJl7YgjjrBevXrZ77//nuF2bN++3TZt2pTmBgAAkGoSGtitX7/edu3aZeXKlUvzuO6vXr067mv0+N6WV0bv6aeftpkzZ9rdd99tH374obVu3dr9rXiGDx9uxYoVi94qV66cKe8PAAAgO+W1EOrYsWP03xpcUa9ePatRo4bL4p122mnplh8wYIDr5+cpY0dwBwAAUk1CM3alS5e2PHny2Jo1a9I8rvvqFxePHt+f5aV69eruby1evDju8+qPV7Ro0TQ3AACAVJPQwC5fvnzWqFEj12Tq7d69291v1qxZ3Nfo8eDy8u6772a4vKxcudL1satQoUImbj0AAEBySfioWDWBTpgwwZ566in74Ycf3ECHLVu2uFGy0rlzZ9dU6vXu3dumT59u9913ny1atMiGDBliX375pV1zzTXu+c2bN7sRs59//rktW7bMBYFt27a1mjVrukEWAAAAYZXwPnYdOnSwdevW2aBBg9wAiAYNGrjAzQ+QWL58uRsp6x133HE2adIku/XWW23gwIF22GGH2bRp06xOnTrueTXtLly40AWKGzZssIoVK1rLli1dWRQ1uQIAAIRVwgM7UbbNZ9xiacBDrAsuuMDd4ilYsKDNmDEj07cRAAAg2SW8KRYAAACZg8AOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJAjsAAAAQoLADgAAICQI7AAAAEKCwA4AACAkCOwAAABCgsAOAAAgJJIisBs3bpxVrVrVChQoYE2bNrW5c+fucfkXX3zRatWq5ZavW7euvfXWW2mej0QiNmjQIKtQoYIVLFjQWrRoYT/99FMWvwsAAIAcHthNmTLF+vbta4MHD7b58+db/fr1rVWrVrZ27dq4y3/22WfWqVMn6969u3311VfWrl07d/v222+jy4wcOdLGjBlj48ePtzlz5ljhwoXdOrdt25aN7wwAACCHBXajRo2yHj16WLdu3ax27douGCtUqJBNnDgx7vIPPPCAnXHGGXbjjTfakUceacOGDbOGDRva2LFjo9m60aNH26233mpt27a1evXq2dNPP22rVq2yadOmZfO7AwAAyCGB3Y4dO2zevHmuqTS6Qblzu/uzZ8+O+xo9HlxelI3zyy9dutRWr16dZplixYq5Jt6M1gkAABAGeRP5x9evX2+7du2ycuXKpXlc9xctWhT3NQra4i2vx/3z/rGMlom1fft2d/M2btzo/r9p0ybLSru3b83S9aeizNjn7Nf02K9ZI7POEezb9Dhmswb7NWtkdbzg169WyaQO7JLF8OHDbejQoeker1y5ckK2JycrNjrRWxBO7NeswX7NOuzbrMF+Te39+tdff7lWyKQN7EqXLm158uSxNWvWpHlc98uXLx/3NXp8T8v7/+sxjYoNLtOgQYO46xwwYIAbwOHt3r3b/vjjDytVqpTlypXLwk5XAgpiV6xYYUWLFk305oQG+zVrsF+zBvs1a7Bfs05O2reRSMQFdRUrVtzrsgkN7PLly2eNGjWymTNnupGtPqjS/WuuuSbua5o1a+ae79OnT/Sxd9991z0u1apVc8GdlvGBnD58jY7t1atX3HXmz5/f3YKKFy9uOY2+GGH/ciQC+zVrsF+zBvs1a7Bfs05O2bfF9pKpS5qmWGXKunTpYo0bN7YmTZq4Ea1btmxxo2Slc+fOVqlSJddcKr1797aTTjrJ7rvvPmvTpo1NnjzZvvzyS3v00Ufd88qwKei744477LDDDnOB3m233eaiXB88AgAAhFHCA7sOHTrYunXrXEFhDW5Qlm369OnRwQ/Lly93I2W94447ziZNmuTKmQwcONAFbypjUqdOnegy/fv3d8Fhz549bcOGDda8eXO3ThU0BgAACKtckX0ZYoFQ04hgZUTV1zC2SRoHjv2aNdivWYP9mjXYr1mHfRsfgR0AAEBIJHzmCQAAAGQOAjsAAICQILADAAAICQI7AAig23HO/Jz/+eefhG0LkJkI7AAgQLUwd+7cmejNQDZ8ziqH9dRTT7n7efPmdWWyNH95TuHfKxczByZZ9xuBHVL+IM4pNCuL8DlkjSFDhtjjjz9uH3/8sZ144onRx1955RVbtWpVQrcNmU8ZumeffdYVw//xxx/txhtvtJYtW9qiRYsszLZu3epKhOzYscNN6amZmfQY9k5Tl2kWK52LdR5O1ilHCeywzyfBZD2Ic8pVtS/UHfwcCPL+vd9//90Fci+88ILVqlXL7e8ffvjBrrzySje1oGbDQfgoQ3fBBRfY4Ycf7mY+0tSUI0aMsKOOOsrCHpzccsst9txzz7ki/1WqVLEZM2YkerNSwlVXXWUdO3a0X3/91Z2Hda646667bNy4cfbVV19ZsqCOHfaZrvDGjBnjpmfTjB/HHHOMezyZr1zCRNmkt956yw499FD3Q3TxxRcnepNC4euvv7ZLLrnEHnvsMWvatKmbovDMM8+0P//80+6++2437SFSn85TyrQoS+XPWR9++KG1b9/eNm/ebC+99JKdddZZrhn+oIMOsjBSIKL3r8zkp59+6qbrHD9+vJ166qmJ3rSktnv3bndhrdmxNE3pnXfe6aY21XlDx1KhQoVc1tfPW5/o30Mydtgnzz//vJUvX95efPFFF2Ccf/75dv/997uTYKIP4rD7448/rFWrVjZ48GBr2LCh+xFSs9GDDz6Y6E1LSdu2bXPNq/q/+Gaozz77zAXLN9xwg7Vu3dqdwHUiFzrWpz6dpxTU6PNeuXKl+0z146xAXnOS6zslCurClO8IHrt6/7r/n//8x90/99xzCer2wh8LCu70G3jdddfZ2LFj3TSlasZX072aZ4899liXCV28eLElnDJ2gLd79253C1q9enWkWbNmkYceeij6WKdOnSLly5ePTJ8+PQFbGV6x+17eeOONSMuWLSNr165199etWxc59NBDI0cddVRk/fr1CdjK1HbvvfdGWrVqFdm6dWv0sSOPPDJSsGBBt091vMsDDzwQKVq0aGTRokXu/j///JOwbUbmGD58eKREiRKRevXqRc4666zIzp073eMffPBBpFKlSu552b59eyRM55K///478tlnn0WWL18efey5556LFChQIPLVV18laAuT387/Hh+yefPm6L91rOTKlSsybdq06GM//vhjpFixYpH777/f7e9EImOHdP3odPv777+jj3/xxRcuDd2rVy9bsmSJy9a9+eab1qdPnzSdzPHv+9HFy36+//77VqZMGXfTFWGNGjVcM/iUKVOsVKlSCdja1KaMnK62CxYs6O6//vrrrhmldOnSrv+M9rMoS6oM6fXXX+/uk5lOXcrKzZ4929577z2bOHGiy7rMmzfPLr/8cpeRadKkicu+jBo1yjZu3Gj58uVzr1u/fr2lKn+8qoVF54muXbvaCSec4Jpgdb656KKLXH9CDRoiI51xP0wZNGiQy+Z/8skn7r7vd+sHtOn/6qupffzII4/Yd999ZwmV0LASCbVly5a4WaKBAwdG2rdvH72Se/rpp12GaMiQIZEiRYpEOnToEFmyZEl0+VWrVmXzlofHrl270tyfOnVqZOzYsZGPP/44+vwtt9wSOfnkkyOHHHJIpEGDBpE333wzuvzXX38d/Ryxb7RPdUWtY/zVV1+NPq793KRJk+j+VYZuypQpkeLFi7vPRb755pvIzJkzE7bt2PfvlD+vKQOr7ErlypVdFtZ7//333eOvv/66u//dd99F6tevHzn11FPdY8ccc0zk7rvvTvcdTRXz5s2LvPLKK5ELL7ww8uKLL0a+//57dx45/vjjIx9++GE0U5knT57IW2+9FX3df/7zn0hObaHaHfNb+Pnnn0eqVq0aadSoUeTRRx91x4zXuHHjyJlnnhltSfGZXv1W9uzZM/L7779HEoXALgdSMKATmP9ye/pylytXzp3QHnvsMZe6l5UrV0Zq1qwZqVChgvth8/TDN2HChMjEiRND0XSRHb788svInDlz0j2uNH/btm0jpUqVijRs2DBy0EEHRZ544gn33Msvv+xS/F27dk3zGp049Njzzz+fbdufSjZt2uT+v23btrjP161bN3LCCSdEm6cUAGjf9+rVK3qxsmbNmkiPHj3cBU2bNm1cIPDMM89k47vAvgo2lcf+QN9zzz3us/NBu3++Xbt27gf6jz/+cPd1TtT57/DDD4/ccMMNkVR778H3rfeg41ZBhvfbb7+54/7666+PBh4XXXRRpGzZsm4faV+o20dG35mw2rx5c7oAXvtU3/1u3bql6bYRDJx1TD377LNpXjtq1CgXQPtjKhEI7HKoYKbC/wi2bt06MnTo0HTLKiPUt2/fyMEHH+x+BP0Ppg5onSSUYaL/0b7RiVP7y9MJ4dprr408/PDD7v8bN250fegGDx7sgjldZcvpp58eOfHEEyOTJ0+O/Prrr5H58+e7E3DTpk1dsIj/+fnnn93+UrYl6IsvvnDPBTMTuXPnjowfPz76Q6bPRv3sgsHbX3/95X70brrppjR9lJCcHnzwwcgll1zizlk+860MrTIpV155ZZplf/nll0ihQoXc5+5/nJWBCWbBkzljF3veDd6fMWOGO2dfc801aZbR90J9DF944YXoaxS8NG/ePNKvX79ITnPfffe5LKb8+eefkdtvv919/joOlOVVn7lg0Kz95Y8J9TVXK0rwvJIMCOxymOAVnQ7ijz76yB2kOoiVclaAIWqKUBChHzRlMnT10aJFi0jFihXdCUBfBHUsf+SRRxL4blLDa6+9Flm4cKH7d7BTrf8sFKDpyk+BQ1CtWrUiHTt2dP9WpvTqq692zSYayKIO4PrxCnbozclif3zVRHLOOedEfvjhB/fjrX2pH3YN+NEx67MVV1xxRaRatWrRANp/HupuoKY5pA5d8Oi8pM/5rrvucp/jSSed5H645cknn4zky5fPBfjB71+fPn1chlwtE0H6AY83mCkZjRs3LnLKKadEzj///Mgdd9wR3W51N9AF4YIFC6LL7tixw+2XSy+9NDowSBmpYJYuJ12oL1u2zJ1/ta/0/wsuuMCdpxcvXuwymWrGzsiGDRvca5QQiZc1TRQCuxwi3lWnTgK62tCPmgIEBQ6lS5d2wZuyd2quVbB39NFHRzMXClJGjx7t0s00v+6d9q2CMY228ydOnWTVrKdRVPLTTz+5IFlXisHP6u2333YnDV15ewo21Fyk1yDtca2TsQ/Y3nvvPdesqh+53r17u/5zS5cudYGcHh8zZkx01JuaqxRU+0y0muvUr85f5CD5xPvxVPcRBXP+vKSLKZ3L6tSpE21KU9O7gn4FN56OgdgWjFSh87YCEo3SVHCnAEPn9PPOOy96vlDf3DvvvDNNFnLSpEmu24e6ecR+n5IhMMlKuwPvT8GYuibpPKvsZmwQpySGRk/rty/4WmU7/cWgWq4UBCYTAruQ0xc1o6YEnfgUuCno0MlNy+kgfffdd11Tn7J0CiB00M+dOzfbtz3V+ZPAdddd5zrlf/LJJ2mu8hR0+Axe//79XR/G2IEoZ599tgtE1NcLGdMxrD6Kuujw1FdOzarHHntstISJbz7RhYv6yIg61CuQ+/TTT6PL6MSdzE1wOVW8TJIPRq666qrIsGHDolk4BezKSgUvgtQZXs3vOs+lmngB1+zZsyPHHXdctIuAunHoeC9ZsmR0EIT6CuriPLZPtVprcnL5kl3//X6r+4svgzNixIg0z6mbi44Xnat1Ia4LAl1wax+rb3myIrALkdgvfvC+rkr0Q6fMhQIM34SnoEOZOY2Oikc/lLoK1gkD+8efHJRFqlGjhuvzo87LoitonUh8/zidXBTYxXbYVlOi6qvp80N6GvWn/abgV01uGr3qMxPq96IfNPUDDTYzqfaimrODTd9qclGwp88ByU+ZFfWNDAZtZ5xxRuS0005zTbEaABEcvazMlf/uqaktlQZG7OkC46mnnnId9WXAgAEumNX703nDU7bpiCOOiHTp0iXNCE4v7Bm6WLqYvvXWW91Ntfz8cTFy5EjXcuJbUvx+1+PKgpYpU8YF0Tofq6k/mRHYhYyaHHzRYF1d6Es7aNAgV4hSo580bFtf8u7du7tl9EOm0VMK8HxWSFd2GpGpIq7KZPjRmdi7jPrlqOlaI4sViHjqmKtRrcrgyeOPP+6aA3x/GL+eeCOy8P+DITQYRRcfuhKPNypSwZ4Cu9iRrBoVqLIWvglOmQ/KmCQffY7Bvku6IFVTqpoe1TdSF6XqC+yDPWXCdb4LUoCvDJ4yLRJshk0lCkKU2Q8WxVW2Wd8BXZjo3B4sGK9yVb65UEW5ldFMdOHcRAfF06ZNc9lM9TtUoKuWFLWK+As/9cVV3+XY16r/pUofqXtGIke77isCuxDRgagvsE5uPlhQOl7ZDH/y09WbAjUFej7IUH+j6tWrR08Yqlun7IVGkJHB2HfBE4GCM2VGg1fIyiIouPZNJMouqf+dfnB8IFK7dm3XsZlmwIwFgzadiIMn2tj9puNXg340CCU4ck2DUdT3SiMGU/WHPuyCF0jq/6hz2rfffutGj+szU1cSnaPUncRf/CjQ0+et0k1qZVDArh9xZbV8JibZBwjofQebDHVfrS0KZnVuUFZOAZ4ok68LRPWpCwZtOs/r2PYzaeREuwLnAvW71D5VEKffyOAIYf1e+kGA6l+bN29e15dc+119EIMX46mCwC5FZfTDr8LBan7yoylnzZrl+ggECwrrJKmMnX4UPZ38lKHTCEJ9CRJZXDGVKa2vJiGdbDVNla6m1albdLLQyVm1//yPiva7mo80os/3AdKVIfZOWbfgIBRdvKirgQqyqh+djn3/uJpSgsVpRRm6nFavKxWpyUwtBwrOVN7ntttuiz6nvr86j/mSHspQ6aK0cOHCruO7r+MWDJRSKZhVIKv+oSoav2LFChfAKvusYMQXy9V7V/kSZSoV7KqvqM4pesz36/XrzQkXjP8EAnb1PdToeGU71WyvPrfaj7rp3KHsnbrFBKsL6Pyh87S6z6i7TLAgfKogsEvxYdrqZxIs1aCDWgexvvgaAKEO4soCBSuLi7JzOiFqGV/eRCdNrRP7JrbJVT8eCih0VahATZkk9c/QZ+HLnejKWk2Avm+d+sLoeQV7OeGkmxn8flKNMnUjOOyww9wJWv/WSVknbP2oKxjwAfPFF1/sHvNFt5H8FLRpdLOCFGW3FcirtqOCd09ZKtUZU98oX55GF6XKZCkTrpHQyZ6hi0cXISrBokBEReOV6Q8GpzrHqAXAl63SPtB3QI9peXXxCHuza7zzb9DSpUtdfT6NGlb2VoNF1A3psssuc11edE4IZvF9P2Zlg3VxrXNyqiKwS1EKGtRnS0FBlSpVXDbIZ9nU/Kfsm37I9COobIVS98EJ49Ucq34ZTAeWeSON1edL+1QnWtGoKXXkVtbO/+gokFPTkTrf+uV0AonXqRl7p/2qMg86nnWB449n/ajps/DNLsrOadSsr9uF5BL7ffK1xXRu8318NShGoxOVhQs2vysTo4LUfhBBrGBB2WQNTvz/NSuNggqVotLFt/qA6gJcg32C52od6wr8fGuA6Hkd32p1ScVg9kD50e1Bl156qWtS1UVe8HdP/RCVzVXlh6A33njDDaYKy3mYwC6FKThQ50998VWfSYGcb5bSAAj131INNJVu0DK60lXwp6uXzp07uyKsYb+qy2zBHwidhDVDhN/n6relgFr9MpT9VHOs5hf0r/H1tVQvUPW1KCGTln6EfLD7b5tIlSFVUEAB7eQWzLIocNMPru8vp5psCu6CI/bViV3nMmViPAVFKj6s71QqtTjEBpu6r3OGso/KTgYvGLUfNHVgMFDTxbrqjvqsdOy6kjWY/Tdi35P6hyurqYEiOh+fe+657hjRuVjNqMG6hqJzs34X1Y9cAbBv2la3GTVlh2WgGoFdCtOPoA5kpZTVWV8da9UspROi+haoX4ZKQYhGDipVrw7jqr6vL0Nw3lfsO3XiVkkBNfXpytD3Y1Ewrf2vKYpUFNcHKaIA22eP1J8jtjBoTqeTrPpGab8F6Udd2YnYzMaeaMCE1hOcBxbJTU1iKkGibIqfGUIXoWpWvPHGG6PL6fNXVxPNIKEf82B/tFTpLxkMZvVvBRa+q4aanFVO4+abb07zGnUxUJ+5YNOyMlFqEfDnnzALBnS6APDlt9QCokytLuLy58/vgt0d/x0MpeNGv3Wxwb7ODeq2oZYTJUZ0HleXpjAhsEtx6hiu9LJSyaIrEVUaV+pe/bt01aJpwUQdcdVkm6pV1pOFRuVp6iJ1wI0NNtSEon0f/NHRiUV9ZHRC8bMbIC39wKmTuy5O1LSifauR2spgqElVmVEfKMfLROgEr5OzZu/Q8a8BRNT+S34K3PV5aSSrn1pP3xM/Gv+hhx5yF0o6dwUvrNQ6oYvTWKnU9Kg+ohq1qo76wdGrGnylfRHsO60gV/tBBXSDAWxOG9GtgQ46VlSzT9RXWckL9Znzxcl3//d8rH2mc4fvk+nPGzrXqJVF/cr1e5kqA2v2B4FditMX23cY93Md6gdNdel0wOtEqVtY+g5kl3hNGTphaISaysfoB0c02ljZBl/FXSdjFbHU1aA+AxUlVnCtzs70Z4zPn1hVmkId5TXtl0Y+DhkyxGUldBJXpXfdz8g777zjOkkr6xdbsw7JITboUjcQfVd69OjhjgG1IKi1Qdm4YB8o9RHWOS74emX19MOcinTRp4sWnUc0mEoZI/XD9TOf6HugYE+1L4NBnL4HOpfHTieYSsHsgVJCQhcA2meqJefLd6kZWudeVYHQ6FdfbPif/+4TLauAOBgk54SCzAR2IaC+BcoS+el0PA3TVjkNPafOxjnhgM4MwROlsm3qCxecZ1EZUu1XNfUpoNZJWc0AytapiUBXijoJX3755e55MqTxxftB0g+7Cgrr5juB6+JFzXTaz76jdLysXby+RkguOgf5fkw6bymoUeYqSCM71VfVTwOngS8KaFLxexTvGNeIVWXldAyrW4ZG/uoivF+/ftGyGwp21U9XQV6Qb5nJSVT3UxlatUD5ovuxlHnTxZ/PfO4OlHfR8aQL6zD2OcwIgV0I6CBW88Upp5wSbX7yB3aw4yjS2tMXXYGcBpioQ7ZGHyv9r5OHaMJnZZS0z3XlqNpz6hujukcaqIK9C56ctc8064aoT5yybspYBJtIlM3QyEdVi0dqUnOqmto10EGUXdEFka836AM+1WdT7U1lXn1To46JPWVsk52f1UfBqgKN2Pei/mDqPuCLxGt5zayhAsypMNNBVvIVHILzPccGzAqIFQyrv903MX3HVepLA1JyUn/b3IaUlytXLrvhhhts586ddu+990Yfk3z58iV465KPLmgkd+7/P/y/+uorW79+ffT577//3tq0aWNr1661N99809544w1r3LixDRo0yFauXGk1atSwwYMH2+jRo+3CCy+0pk2bWpUqVaxgwYLWoEGDhL2vVKLjc+HChW5/6dj98ccfbfHixVa5cmXr0KGDlSpVysaOHRtd/rjjjrPTTz/dfTYvvfSSe2z37t0JfAfYk3ifzRFHHGFbtmyxmTNn2rJly6xo0aLWqlUrGzlypHte3x856KCD3Hf00UcftRUrVrjHpk2b5r5zqXJu8datW2cXXHCBXXXVVe5+uXLl3LnGn5937Njh/n/jjTfakiVL7OWXX7ZVq1ZZ2bJlrUuXLla4cGF3y8l0zNSqVcv+85//uPvPPfec9e/f38455xw74YQTbOrUqW4fXXrppW6/3nnnnfb777/btdde646h1q1bu89B55acgsAuJHTQtmvXzgUgsScXpP3B8SfVV1991erUqWMdO3Z0wdldd93lHs+bN6/Vrl3bPa/AQydaBRO//PKLC0IkT5489tNPP9kXX3xh48aNs7POOsuaNGliFSpUYP/HiLc//v77b3dy1v5dtGiRC5pr1qzpnjv33HPt6KOPdgG1P5lL27ZtrUiRIu6z0OfoA3Mkzq5du+I+rs9GP6b6DumH2X+vBg4caHPnzrXp06dboUKF3Hfvm2++sUceeST6WgX5CnTmzJlj77//fvT7luzBvI5zf27xypQpY0cddZQtX77cXn/9dfeYAraHHnrINm7c6C689Trti/Lly7uLTF1MigJZXajn1Itzf95o3ry5O550rBQvXtztF11068JAAfDFF19sn3zyiQvyzj//fHfxp/P6jBkz7MQTT3TryHH7MNEpQ2Qe+tDtG5UM0KhWpedVgkSzEahpRPWN/AAU9ddS527fHKvnVQ1epQj8QAnVlVJfMM3sQYf9+J566ilXy8/z5RrU/1P9q9R1IHjc+uZX9SVSvxo/+s3TKLic0Fk8DOcelZ5Q37FgHTpRqSA1q6u4tLqKqF+lml7V3UF96zTCUZ3dNRm7upekEs3RqioE6q4RHLHdrl07189Lx7f64Ko8h8pU+XmjNRBE5xo1Jer/fq5vyUl9wzKigWeTJk1yXV90Dgk2y2qgmp87V/t32bJlrv9mTkZghxxF/VUUjGmEVXBAhEa2aqRasIq5gjUFgOpDF5x3V495ql2H/9E0Tr4DswIw/Vhrxgc/2bYGlPh+L6VKldpjCROdrFV3MbZKPJKHOvdr1LfK0fgSP75fr75f+vw0l6nvY+ZHtKo+nS6W/KhPzbagshQ6Pnzwr+BPQU6yXrT6ckdBGuChaatUQzRIs8v4EZ2ii0MFJArwNAhLF5XqW6iSPSo6HMYSHPH8m/epY0KfgcreBMvFgD52yGFKlCjh+nCp2U9NPd6ECRNcM8rHH3/sbrro0f+3b9/ummlF/X3ULLBgwQKX5hef6sf/N8u99957bt9q/6n57KKLLnL76vbbb3dN1trP8s8//1ilSpVsypQp7r5vVlWfIzXNyXnnnef2vZq3kZy+/fZb27Bhg2tK1Pfq119/dX3kRI9dd911rmnxo48+ir5G3UWOPPJI1zT5zjvvuMfUV/WOO+5wx0fVqlVdPyr1w1P3Eolt4kwk38+2ffv29sILL6R5Tl0y1D9X547PPvss+rge0/t69tln7bfffnPNhq+99poNGzbMTjrpJPvuu+/slFNOcc+pW83WrVst7HSOUPO8vP322/b555+7feuf25u//vrL7r//ftc3U903EJDoyBLIbsoSqclHBXFV/6x+/fquuVWjqjRkXk1BugJ88MEH3eOalkrNiSpzoqZFagJG0mXZ/L99M6nPxKgpVZkKZSWCzSMaAakaXir7EBzFpqyFijkH57tE8vEZNNVU0+erpkdNrq7PM3bydH32qjHop95TM5oeU1cIZWX9tIbK6ml0tDLixYoVS9rZAFT+SFNQ3X///S7rrObB4Cwzvh6jso/BTKPeq2qqxc4qEcz2KYunsh45hUrdaBYI3ZTdVWUB39UlHh1nmkZM2V0VL1eNw2AxePw/AjvkSGr6UdOrJorWnLvBkgKqUae+PTrpaJYJNa2o6TbYVywni20W0/Ro6m+oCcgV2KnfnH6cX3nllejJWDW5tC+DM2+oaVsBtpry9COoPlUKqvv06ZNjmqJSSbzmcgU5CmLUfKrZIhTs6Psybty4aD8x1aFTc9lZZ53lLqR69erlmmFVvy32c1YTvfqyJvv0YCrHo75zzz77rCuMqwLKQaopqmNe5xlPTdKawurUU0+NNk2ruVrdF/R9Cc4SlBPonKsAX/Pi+nNKp06d3L5V/8t4VPZIBcx1Uaip5RAfgR1yJNXHUiduBXA+qPN97nQ1qJOsz8zFVnrH/1Pgpj5CqvOnORk1b6Uymuocrh97/dj5TIam+tKPmgLA2PpTqgmobKk+j2AfRyTnLCwaIBCkz94H8aL5kzXIqFu3btHadOqvqmNCx4iCGPVpDa5/f+YCzk6xA3W0rTp3qMiwAlD9W0GIspYKOHx/XM1Io2XKlCnjltNzZ555puuTGzsNmPqJqUamL04cNhkNdtJ79tPCaRllMosUKeL2255q92k2GuwZgR0iOX3GjjvuuCP6mLIOmi1CWYVkzxokioK1Dh06uMEQaqZWIKd9qWY4ZUE1+4YCOBViVQZHfLCnAsO+mTU4zQ+SnzKx+tw1X2nwh1dNsBpdrs/TT6quLIyCHV04zZ8/3y2ngCY4WjTZgrggbVswIAkO/hCNcg0OkNA5RN8HNSn6pkGNrFeBYWXulJkKznebU0Z2Bz9jfe+DA9bU9KzBVSpArCydjh11xcC/R2CHSE6fsUNNI2pG1OhLP4djbPVy/M/ChQtdlXz9yAcpK6OmVJUqUZOrRjTqxK19K2q2Un9G/Shq+jX9EPpyD0je74iyVIMGDYpm4fSD7MsCibKt6mum51XCwwfumllC2VyV8Iid7i1VAhs1t6qpVU1/frSuqJ+XLlRUWkNleQoXLuwmoddyOsaDozSDfXJzQukSHTPBgE6Bbr169VzQq5lHfAvISy+95GbXUOuIgrtgJlMXhD4LnMwXAMmKUbGwnD5jx7Zt21yh3LPPPtt69uxp8+bNcwUuEV/dunWtc+fOrmDzxIkTo49Xq1bNFQLVaFcVElaxUO1bv4wKiQ4YMMDy58/vntcIysMOOyyB7wSxYkcj6juigq+q7v/iiy+6z1IV//UZBwvIqtiuRoFq1Oehhx7qRkir4K5GxOpWsWLFNOv1BYeTkX9f48ePdyN4VWRYx7ufJUIOOeQQV2hZI8D13ubPn2+9e/d2o2Q1uvWBBx5wM6uIXi/aJ2Evqq33qGMmOIpZo+E1+8OIESNcYXKdF1RgWLOOaDYSFXbXqGE/mlrH0SuvvOIKl8cr+ox9kOjIEkg0XWmrf4cfnYe9UwZGfeKUffOd6FWMVs3YwWa6G264wQ1GCdaio4k7+SiTFK8/mW9m1ICIYHOkz+SJms+UkVHx6Iwkc4YuXkZIXQfUfKrMXDyqxafstAaDeH5/qDtHsMkxp/XBlDvvvNPNf6vBIBoM5ftlar8ou+kLj6swszKeqj6g7i8aPKHMb79+/ZL6mEl24b58APaBam0NHz7cChQokOhNSRnKUmiKL023pqybrsh79OjhpgFTrUA/9ZPqk6nelJ8mSZSxQ/JQVkSZJGXRVKtx0qRJrq7an3/+6Z7XHNSq56jpm/7bfcdlUXz2qXTp0rZ69WqXnc1IMmbo9D58hin4mChLqRp9mtrOP66bP67r169vJUuWdFOF+ef9/tBUV6rhl9F0a6nM7x9NCXf33Xe7f+t9+/eu2oOqZ/jYY4/ZDz/84KYN1BRxfkov7RfV7nvwwQddy4jq/ik7p4yoMnaqSadp1e65556kPGZSxf9XBwRyMFL9B0ZNKpqjUYVmfROdfvh8cWJRM8uYMWNccx2S9/jXZ3b99dfbE0884YoHq+iwmlRVQFjNZGpG0w9wsBCsJlqfOXOmnXbaaW4SdjWzpdr71nGqLgEqiKw5XXWRcvjhh7sCwdon/mLPnyP0fwVsuqnrgZoLM5q3OGyBid6zf0/vvvuuK7LsH1dQf9ttt7kCywp4VWRcx4SOKV3sqXn15JNPdsvrsYcfftg1V6vAsC4MdGGNzEPGDsABUebNz+KhH3jxmR8J9sFCclOWbvbs2fbWW2+5GQCUkdEsIgMHDrQqVapYt27d7PLLL3dZLAV0mzdvtjvvvNOmTZtmW7ZscRmuFi1aWKoZOnSo6+el9z1o0CA79dRTXRDSsmVLN+H8M88847KV/njWvx966CE3Y4KeVxAc9n5zPkup77UCfgX56o+sWUHU71CPK4hbt26d64upzJvui2ac0fN6XM97Y8eOdf0xg7P/IBMlui0YQGpTHTr1k9FoSWEUW2qU8Ag+rlIT9913n7v/wQcfuFI1Ksqt4tO+35hGgaovlJ5T/ULNvqC+lak64lPbrtHdM2bMiD7m6+ypZI/e+0EHHRQZNWqUq1Wn0a1Dhw51o14XLFgQ+j5gsd9jvXfNla2i4toX6lOpcjaqXSmaWUT7U31vg4XINT+uqg0Eax3K2LFj6decRXLpP5kZKALIWZStueyyy9xI4kceeSR0TVBhEBxdqBGs+vfBBx/ssk1qSuvSpYvVrl3b9a1Tf8hevXrZTTfd5LJSamJV3ye9Tk1smitZI17VFB+77mTj+8XFOyavueYal3l88skn7f3333cZu59//tnuvfde69ixo9s3al5UE7SW03tUNkr9x/wc0f7nM1nf/4EKNi9rHlf1lfvjjz9s8uTJ0SZY9aHr06ePO0b0vdf/lcXVHLh9+/Z12XxPzbDqX6fmV0bCZ4OsihgB5ByffPJJuor6SHyWJfa+RilrNgRl3Tp27Bid9kujEZWdUpFpzYQQHP2sqbBWrVoV9+8lc9Yq+N71PpV18+/XZ5qVhVQdPs1b27dvXzcaVvyoVmUhtQ+U1dN0Z/HWHVaqP6nsZf78+SNly5aNnH322elGwWpeYBVgji1EHjvfs2pbah5u1f1D1gt35wAA2eL444+P1qFC4jJTPnOkkazi76vOmjq8q/+Y6rOpz5wGvqi2oEY2K0OnTuzKrKhGmyhTp/5kyswE+0f5vyfJnJ31711ZJGUY27dvb8cdd5wbECLqH6cMpPaNBkHcd999ruO/snPK1KnPobJWGgGuPnca+S3//PNP6DJ0sX766Se3fzSgZOXKlW5QzUcffeQGQmif+ONLWVv1UVSWV6Nftf8uvfRS93r1v/Q0AEf7U/01kQ2yIXgEAGSR2Cr/ykCp/9L27dvdYx9//HF0uqvgpPTqY1anTp3IkCFD3H1lrLSM+kmp9phmjahVq5Z7fapkjWfOnBnNymm7VSdNGST9X/O4ahYJ9ZGbPHmyyy4pQ6k6i8o8KuOsfaYp01SXT1mmnCw4K4yylpdcckl0btdgtva1115zfWz79+8ffU798DTjSDBrh+xDYAcAKU6d1dX8pUnUNZXbrbfeGp0sXXP79uzZM5IvXz4332swGLzuuusijRo1csGQmh8/++wz9wPtg8NUoIEMKiasQPTqq692c9MqQFMwqybWwYMHR5dVkWW9NwUimzdvdoGggrhy5cq5oE8DQjQwJDigIicLDohRIWoNnvGDbIJdL3whcr/fNLCCuaATh8AOAFKYArL27du77JP6RQVnhfDmzJnjZkrwMyns3LnT/V/9zhQALV++PMP1+2WTiQ9Mx40b5/oMKqDTvK7KMvnn1P9L780HIt7UqVNd1k7/F82U8vjjj0eGDRsWefTRR+P+nZzM7wONjNaMEepvp38HgzsdX8r0au5tJB6BHQCksI8++siVk9A0VxmVHFEG6/rrr3dB0MqVK6OPT5o0KXLYYYe5Tu2xQUyyly/RNFVq7nvggQcyXEZNy23btnXlOYKv08Tz06ZNS6lgNhmoqV8Zzssvvzzd4JlUabLPCRg8AQApTOVKli5d6mZCUMd2zaTw6KOPummZNF2epmjSwBaVoFDZEs0eMXLkSNe5/dZbb7WGDRtapUqV0g0ISPbCu+qMr8EPJ510UvQxlSvRYA8NEhGVJlH5Dc2O4mmwiKb9ije1nR8UogLESE8lca666ip76aWX3JRgGjyjwSRCIfLkQR07AEhhv/zyi5133nm2adMmN/pTIxI1mlFz9CrIU726W265xc3HOWHCBLviiivcvzUNlGYNueOOOywVadRumTJl3MjMM8880wVwer9r1651o1wbN27sZpTQFFaa5UC1+lSDTaNfixQp4kZ4aiQw9o+CZ9X5a9CggbuAQPIhsAOAFKfJ11VoV3N1amL1ChUquMBGUz5p+ieVmRg3bpz9+eefruyHAhoV3o03D2gqeeGFF1xJFpUsUeauVatWbq5XUTayRo0aLvgoVqyYmy6sVq1abt8o0MWB08UEpUuSF4EdACSZ/ZnNwS+b0WuOPfZYF+Boonsto3lgzznnHFfP7ZRTTnFNaanc9KhMpZ+vNPherr76ajfvrZoMNcuE5jN++eWXXXOipPr7BjKS3J0oACAH2p8CuHtaVn3LVLhYTWd+WRUh1gTuF154oXss1YMb9Zfzk87796Iiw2oyPP300939MWPGuCbap59+2j0XXBYIGwI7AEhCmrtU1f4930k9o0YWH+ApmFN/M/U9u+SSS9xgCTXHehpAoaZIzf8ZJupTqBkylJlTk+yaNWusU6dOrplZA0GGDRvmBo2o/x0QZlyyAEAS0khXjUD8+uuvXdDmM0wKXsqWLZtmonZv4cKF9uqrr7rRohoY8f3337sRrxJsqlXHd93CYsOGDdFJ57UP9O/Ro0enWUb7UvtMfQ+BMKOPHQAkER+w6dRcqlQp14yozJvmdr3yyiutUaNG9tRTT8V9rbJTKueh1x566KHRx7S+sM9vqj6Dan5V/0HN7xocFBIvCAbCisAOAJKwlIeaTFUvTOVJjj/+eNcs26tXL9eEWqJEib2u478F6HNkQJNTglkgHppiASDJKKiT//znP7Zx40bXL0xNsvtTYkJBTU4MbBTMpmLpFiCz5LxLOQBIclOmTHF94zQI4u6773b97fzgCexZTgxmgSCaYgEgi+k0q35e+5JJUvHXyy67zI1m7d69u8vetW3b1q1DgR4A7AmBHQBkoWDH/a1bt9rvv//u+shpqq+MaLlChQpFO/9rJGy5cuVsxowZ0dpsABAPTbEAkIV8UHfnnXe6EiQqFqySG7NmzXKBm8ReXyuoEwV1O3fudHOiqoyJ5joFgD0hsAOATBQbpCljd9NNN9nzzz9vDz74oBvp2rJlS+vdu7dNmjRpr/3CDjroIPd/FRkuUKBAhgWKAUAI7AAgk2iAQ2yQtmXLFvv444/trrvusvbt27vHFixYYH/++aeVLFlyv/8GgwMA7AmBHQBkwsAI0ewQajqdOHGifffdd+4xlSpREHfaaae5yegPP/xwq1Gjhn366afWpk2bBG89gLAhsAOA/fTYY4/ZW2+9Fc2g+X50DzzwgBvk8Oyzz9pnn33mHtPUXZrHtEiRIrZkyRL3uieeeMIqV65sP/30k2uaVa06AMgMBHYAsJ+mTp0abUb1fd40N+m4cePsoYcectNb+blL1Tzbo0cPNyDihRdeiA6A0OMTJkyw999/P5rxA4B/i3InALCPfPmR4NRfGtCgrF27du3cHKUK7JSBU5OsAjbN97p8+XI766yzXImT1q1b25FHHmn33nuvW07BICVMAGQWMnYAsI+CQd3kyZPdSNWvvvrK3ddMERokcfPNN9vll1/uMnbqT6cBE2qeVRPsUUcd5eZ8HTVqlJ144oluyjCCOgCZiYwdAOyBbyb1/eg8jWxV2ZIbbrjB+vfvb4sXL7Z77rnH9ZtTVk5NtQrkjj/+eHvuueesU6dO7nXK5G3fvj1aoDg2CwgA/0bef/VqAMghs0b88MMP9scff1jdunVdfzkNirj44otdLbpmzZq5DJyaYTUy1tuwYYM1bNjQNdd6el616bRuNeES1AHITDTFAsAesnTqB3f++ee7zFvXrl3t1FNPtbFjx7rnhw4datu2bXMjWzXtl4I29bv7+eef3ahYzfGaL18+O/bYY9PVodO6qUkHILMR2AHAf40fPz4adKmXippJb731Vlu7dq2rO6fZIxTYDR482F577TUrWrSoq0335ptvuv51on/fcsstbjDFEUccYR9++KFVqFAhwe8MQE5BHzsAMLPvv//e6tSpY4MGDbIhQ4a4wE5ZOI1gve+++1y2zjev3njjjTZz5kyXmRM1w5YvX97uv/9+13dOwZyaag899FD3PP3oAGQXMnYAcpSMrmU1G4Sm/dIACDW/qpl0x44ddsghh6RZrlixYnbZZZe5JthXXnnFPTZw4EBX205ZPT1/zjnnuKBOTbq6EdQByC4EdgByFAVs6genIE4DH7z8+fPbBRdcYNWrV7crrrgi+pgycF9//bXL3vnXlyhRwg2A0PNyxhlnuHImF154YZq/pSbd2NG0AJCVOOMAyFE040O/fv1c37lLLrnElSv55JNP3HNVqlRxdeg0Q8ScOXOsTJkyrlbdrFmz7NVXX42uY/369S6w802totInQu8WAIlEHzsAOY6m/Lr77rtty5Ytrt7cF1984e6rCbV48eJulojffvvNZerUlNqlSxc3OEKlS9Tn7tFHH3XLPvjgg670CQAkCwI7ADmSsnbfffeda3ZdvXq1C9KUhXvyySddvbrzzjvPzRCh/nTK0H3wwQf2+uuvu4BPAylUww4Akg2BHYAcSVOBqdlV87s+8cQTtmbNGtc0qyBO/exUf2727Nm2bNmy6GtiR7cy2hVAsqGPHYAc6eijj7ZWrVq5rJ2ydJrPVaNcVdpk/vz5boTr8uXL7c4774y+xgdxCuiC9wEgWRDYAcixOnbsaFWrVnUzR6iJVSNgVYD4vffes+uvv95NH6YRr7EI6AAkK5piAeRoKnmiKcI0U0T//v0TvTkA8K+QsQOQo7Vv397q1atnzzzzjC1YsCBueRQASBV5E70BAJBIKjKs4E5TglWrVi3d83nzcpoEkDpoigUAAAgJmmIB4L9UjBgAUhkZOwAAgJAgYwcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAWejkk0+2Pn36ZPp6hwwZYg0aNMj09QJIbQR2AHKsrl27Wq5cuezKK69M99zVV1/tntMy+2LWrFlu+Q0bNmTBlgLAviGwA5CjVa5c2SZPnmx///139LFt27bZpEmT7NBDD03otgHA/iKwA5CjNWzY0AV3U6dOjT6mfyuoO/roo9NMNzZ8+HCrVq2aFSxY0OrXr28vvfSSe27ZsmV2yimnuH+XKFEiXaZPr+3fv7+VLFnSypcv75pRg5YvX25t27a1gw8+2IoWLWoXXnihrVmzJs0yI0aMsHLlylmRIkWse/fuLvgEgFgEdgByvMsuu8yeeOKJ6P2JEydat27d0iyjoO7pp5+28ePH23fffWfXX3+9XXLJJfbhhx+6wPDll192y/3444/222+/2QMPPBB97VNPPWWFCxe2OXPm2MiRI+3222+3d999Nxr0Kaj7448/3Lr0+M8//2wdOnSIvv6FF15wweBdd91lX375pVWoUMEeeuihbNgzAFINc8UCyLGUVVOfuAkTJrjgTEGZ1KpVy1asWGGXX365FS9e3B555BGXbXvvvfesWbNm0dfr+a1bt7pmW/WxU9buzz//dK8JDp7YtWuXffzxx9HHmjRpYqeeeqrLwimQa926tS1dutRtg3z//fd21FFH2dy5c+2YY46x4447zmUPx40bF13Hscce67J2CxYsyKa9BSAV5E30BgBAopUpU8batGljTz75pOlaV/8uXbp09PnFixe7AO70009P87odO3akaa7NSL169dLcV8Zt7dq17t8//PCDC+h8UCe1a9d2waGeU2Cn/8cO8FCA+cEHHxzwewYQTgR2APDf5thrrrnG/TuYGZPNmze7/7/55ptWqVKlNM/lz59/r+s+6KCD0txXHzw1wQJAZqOPHQCY2RlnnOEycDt37rRWrVqleU4ZNAVwGuRQs2bNNDefacuXL5/7v5pd98eRRx7pmn1189QUqyZi/V2/jPrnBX3++ecH/F4BhBcZOwAwszx58rgmT//vII1E7devnxswoUxb8+bNbePGjfbpp5+6UaxdunSxKlWquEzcG2+8YWeeeaYbOatRrnvTokULq1u3rl188cU2evRo++eff+yqq66yk046yRo3buyW6d27t+sPqPvHH3+8Pffcc24AR/Xq1bNobwBIVWTsAOC/FKTpFs+wYcPstttuc6NjlUFThk9Nsyp/ImqiHTp0qN18882uLIlv1t0bBYOvvvqqK5Ny4oknukBPAduUKVOiy2iErP62SqY0atTIfvnlF+vVq1cmvWsAYcKoWAAAgJAgYwcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAACFBYAcAABASBHYAAAAhQWAHAAAQEgR2AAAAIUFgBwAAEBIEdgAAABYO/wfpRFBIxoGoaQAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "# Create a simple bar chart for accuracy comparison\n", + "plt.figure()\n", + "\n", + "# Use clean method names for better readability\n", + "method_names = results_df[\"Method\"].replace({\n", + " \"none\": \"Baseline\",\n", + " \"time_stretch\": \"Time Stretch\",\n", + " \"pitch_shift\": \"Pitch Shift\",\n", + " \"noise\": \"Noise\",\n", + " \"specaugment\": \"SpecAugment\",\n", + " \"noise_specaugment\": \"Noise + SpecAugment\"\n", + "})\n", + "\n", + "plt.bar(method_names, results_df[\"Accuracy\"])\n", + "\n", + "plt.title(\"Augmentation Methods Comparison (Accuracy)\")\n", + "plt.xlabel(\"Method\")\n", + "plt.ylabel(\"Accuracy\")\n", + "\n", + "plt.xticks(rotation=30)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "39cba92a-8ce4-4efb-a5c3-e53be0f5fd51", + "metadata": {}, + "source": [ + "### Accuracy Comparison\n", + "\n", + "The bar chart shows a comparison of model accuracy across different augmentation methods.\n", + "\n", + "From the graph, it is clear that the noise augmentation method achieved the highest accuracy. This supports the results observed in the benchmark table, where noise performed better than all other methods.\n", + "\n", + "The baseline model and pitch shifting produced similar accuracy values, suggesting that pitch shifting provides only a slight improvement compared to the baseline.\n", + "\n", + "SpecAugment and time stretching resulted in lower accuracy, suggesting that these methods may have distorted important features in the audio data.\n", + "\n", + "Overall, the graph supports the earlier results and shows that noise augmentation is the most effective method for this dataset." + ] + }, + { + "cell_type": "markdown", + "id": "1eb83fad-11cc-4e44-bdc5-6575cd1d0a87", + "metadata": {}, + "source": [ + "## Results and Discussion\n", + "\n", + "The results compare the performance of each augmentation method against the baseline model using the same dataset and CNN configuration.\n", + "\n", + "The baseline model achieved an accuracy of 0.286 and an F1 score of 0.167. Pitch shifting produced similar accuracy but showed a small improvement in F1 score. Time stretching performed worse than the baseline, indicating that it may negatively affect important audio features.\n", + "\n", + "Noise injection achieved the best performance, with an accuracy of 0.393 and an F1 score of 0.328. This shows a clear improvement over the baseline and suggests that adding noise helps the model generalise better.\n", + "\n", + "SpecAugment and the combined method (noise + SpecAugment) resulted in lower performance compared to noise alone. This may be due to excessive distortion of the audio signals.\n", + "\n", + "Overall, noise injection was the most effective method in this benchmark, while other methods showed limited or inconsistent improvements." + ] + }, + { + "cell_type": "markdown", + "id": "2a6677a2-cf5e-4883-b50a-0f20dfb93c59", + "metadata": {}, + "source": [ + "## Final Recommendations\n", + "\n", + "- Noise Injection – Keep (best performance)\n", + "- Pitch Shift – Defer (small improvement only)\n", + "- Noise + SpecAugment – Defer (not better than noise alone)\n", + "- SpecAugment – Drop (low performance)\n", + "- Time Stretch – Drop (worst performance)\n", + "- Baseline – Reference only" + ] + }, + { + "cell_type": "markdown", + "id": "8a0f17f8-2fc2-468e-8ccf-2c2217245911", + "metadata": {}, + "source": [ + "## Conclusion\n", + "\n", + "This sprint focused on benchmarking selected audio augmentation techniques identified in Sprint 1 using a CNN-based model.\n", + "\n", + "The results show that different augmentation methods impact model performance in different ways. Noise injection provided the most consistent improvement and will be carried forward to Sprint 3 for further optimisation.\n", + "\n", + "Other techniques such as pitch shifting may require tuning, while methods like time stretching and SpecAugment did not perform well in this setup.\n", + "\n", + "Future work will focus on refining the selected methods and exploring ways to improve overall model generalisation." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python (projectecho)", + "language": "python", + "name": "projectecho" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.25" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 5180d70b5e228459576a5e9bfa245f41807c817a Mon Sep 17 00:00:00 2001 From: kiran Date: Sun, 3 May 2026 10:51:18 +1000 Subject: [PATCH 3/4] Updated Sprint 2 notebook --- Sprint2_Augmentation_KD.ipynb | 81 +++++++++++++++-------------------- 1 file changed, 34 insertions(+), 47 deletions(-) diff --git a/Sprint2_Augmentation_KD.ipynb b/Sprint2_Augmentation_KD.ipynb index fe7b4ac22..d0fe09b94 100644 --- a/Sprint2_Augmentation_KD.ipynb +++ b/Sprint2_Augmentation_KD.ipynb @@ -10,6 +10,7 @@ "# Introduction\n", "\n", "This notebook presents a limited augmentation benchmarking study using selected methods identified in the Sprint 1 augmentation strategy survey. The aim is to evaluate the impact of different augmentation techniques on model performance and determine which methods should be used in future development.\n", + "Model performance is evaluated using Accuracy and F1 Score to ensure a balanced assessment of classification performance.\n", "\n", "The methods tested include:\n", "\n", @@ -18,6 +19,7 @@ "- Pitch shifting\n", "- Gaussian noise injection\n", "- SpecAugment\n", + "- Combined Noise + SpecAugment\n", "\n", "To improve the technical quality of the model, a Convolutional Neural Network (CNN) is used with Mel spectrogram inputs. This approach is more suitable for audio classification, as Mel spectrograms represent both time and frequency information, allowing the CNN to learn more meaningful patterns compared to simpler models.\n", "\n", @@ -283,45 +285,11 @@ "source": [ "### Dataset Preparation for Augmentation Benchmark\n", "\n", - "For each augmentation method, the dataset is prepared using the same set of audio files and labels. The selected augmentation is applied during feature extraction, ensuring that only the augmentation method changes while all other factors remain consistent.\n", + "For each augmentation method, the dataset is prepared using the same set of audio files and labels. The dataset is first split into training, validation, and test sets to ensure a fair evaluation.\n", "\n", - "This supports a controlled comparison, as required in the task, where the model architecture, dataset, and training parameters remain the same for all experiments." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "bf0e838d-6017-449d-a427-1996a7ecf4a4", - "metadata": {}, - "outputs": [], - "source": [ - "# Prepare Dataset for One Augmentation Method\n", - "\n", - "def prepare_dataset(augment_type=\"none\"):\n", - " X = []\n", - " y_data = []\n", + "Augmentation is applied only to the training data, while validation and test data remain unchanged. This ensures that the model is evaluated on clean, unseen data.\n", "\n", - " for file_path, label in zip(audio_files, labels):\n", - " try:\n", - " # Extract spectrogram with augmentation applied\n", - " spec = extract_mel_spectrogram(file_path, augment_type)\n", - "\n", - " X.append(spec)\n", - " y_data.append(label)\n", - "\n", - " except Exception as e:\n", - " print(\"Skipped:\", file_path, e)\n", - "\n", - " # Convert to numpy array\n", - " X = np.array(X)\n", - " X = X[..., np.newaxis] # Add channel dimension for CNN\n", - "\n", - " # Encode labels\n", - " label_encoder = LabelEncoder()\n", - " y_encoded = label_encoder.fit_transform(y_data)\n", - " y_encoded = to_categorical(y_encoded)\n", - "\n", - " return X, y_encoded, label_encoder" + "This supports a controlled comparison, as required in the task, where the model architecture, dataset, and training parameters remain the same for all experiments, and only the augmentation method is varied." ] }, { @@ -974,7 +942,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 13, "id": "c50f8576-7b3e-4f14-a14c-f9e69a4ab77c", "metadata": {}, "outputs": [ @@ -1010,6 +978,7 @@ " Method\n", " Accuracy\n", " F1 Score\n", + " Decision\n", " \n", " \n", " \n", @@ -1018,49 +987,55 @@ " noise\n", " 0.393\n", " 0.328\n", + " Keep\n", " \n", " \n", " 1\n", " none\n", " 0.286\n", " 0.167\n", + " Reference\n", " \n", " \n", " 2\n", " pitch_shift\n", " 0.286\n", " 0.221\n", + " Defer\n", " \n", " \n", " 3\n", " noise_specaugment\n", " 0.214\n", " 0.129\n", + " Defer\n", " \n", " \n", " 4\n", " specaugment\n", " 0.179\n", " 0.077\n", + " Drop\n", " \n", " \n", " 5\n", " time_stretch\n", " 0.143\n", " 0.145\n", + " Drop\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Method Accuracy F1 Score\n", - "0 noise 0.393 0.328\n", - "1 none 0.286 0.167\n", - "2 pitch_shift 0.286 0.221\n", - "3 noise_specaugment 0.214 0.129\n", - "4 specaugment 0.179 0.077\n", - "5 time_stretch 0.143 0.145" + " Method Accuracy F1 Score Decision\n", + "0 noise 0.393 0.328 Keep\n", + "1 none 0.286 0.167 Reference\n", + "2 pitch_shift 0.286 0.221 Defer\n", + "3 noise_specaugment 0.214 0.129 Defer\n", + "4 specaugment 0.179 0.077 Drop\n", + "5 time_stretch 0.143 0.145 Drop" ] }, "metadata": {}, @@ -1080,6 +1055,18 @@ "results_df = results_df.reset_index(drop=True)\n", "\n", "print(\"\\n Benchmark Results Summary\")\n", + "# Add decision column\n", + "decisions = {\n", + " \"noise\": \"Keep\",\n", + " \"pitch_shift\": \"Defer\",\n", + " \"noise_specaugment\": \"Defer\",\n", + " \"specaugment\": \"Drop\",\n", + " \"time_stretch\": \"Drop\",\n", + " \"none\": \"Reference\"\n", + "}\n", + "\n", + "results_df[\"Decision\"] = results_df[\"Method\"].map(decisions)\n", + "\n", "display(results_df)" ] }, @@ -1195,7 +1182,7 @@ "\n", "SpecAugment and the combined method (noise + SpecAugment) resulted in lower performance compared to noise alone. This may be due to excessive distortion of the audio signals.\n", "\n", - "Overall, noise injection was the most effective method in this benchmark, while other methods showed limited or inconsistent improvements." + "Overall, noise injection showed the best performance in this benchmark, while other methods showed limited or inconsistent improvements." ] }, { @@ -1210,7 +1197,7 @@ "- Noise + SpecAugment – Defer (not better than noise alone)\n", "- SpecAugment – Drop (low performance)\n", "- Time Stretch – Drop (worst performance)\n", - "- Baseline – Reference only" + "- Baseline – Reference only, not an augmentation method" ] }, { From f8a59e01ab77d8af8fa7f5d32ef139d8d3f4b6b1 Mon Sep 17 00:00:00 2001 From: kiran Date: Sun, 3 May 2026 11:37:48 +1000 Subject: [PATCH 4/4] Add Sprint 2 augmentation benchmarking README --- README_SPRINT2_AUGMENTATION.md | 58 ++++++++++++++++++++++++++++++++++ 1 file changed, 58 insertions(+) create mode 100644 README_SPRINT2_AUGMENTATION.md diff --git a/README_SPRINT2_AUGMENTATION.md b/README_SPRINT2_AUGMENTATION.md new file mode 100644 index 000000000..ebd675041 --- /dev/null +++ b/README_SPRINT2_AUGMENTATION.md @@ -0,0 +1,58 @@ +# Sprint 2: Augmentation Benchmarking + +## Overview + +This task benchmarks selected audio augmentation techniques identified in Sprint 1. The aim is to evaluate how each method affects CNN model performance. + +## Methods Tested + +- Baseline (no augmentation) +- Time Stretching +- Pitch Shifting +- Gaussian Noise Injection +- SpecAugment +- Combined Noise + SpecAugment + +## Approach + +A controlled experiment was completed using: + +- A fixed subset of the dataset with 5 categories +- Mel spectrogram feature extraction +- A CNN model with the same architecture for all methods +- The same training settings for each benchmark run + +The dataset was split into training, validation, and test sets. Augmentation was applied only to the training data, while validation and test data remained unchanged. + +## Evaluation Metrics + +- Accuracy +- Weighted F1 Score + +## Results Summary + +| Method | Accuracy | F1 Score | Decision | +|---|---:|---:|---| +| Noise Injection | 0.393 | 0.328 | Keep | +| Baseline | 0.286 | 0.167 | Reference only | +| Pitch Shift | 0.286 | 0.221 | Defer | +| Noise + SpecAugment | 0.214 | 0.129 | Defer | +| SpecAugment | 0.179 | 0.077 | Drop | +| Time Stretch | 0.143 | 0.145 | Drop | + +## Key Findings + +- Noise injection showed the best performance in this benchmark. +- Pitch shifting produced the same accuracy as the baseline, with a slight improvement in F1 score. +- SpecAugment, time stretching, and the combined Noise + SpecAugment method performed below the baseline. + +## Final Recommendation + +- Keep: Noise Injection +- Defer: Pitch Shift, Noise + SpecAugment +- Drop: SpecAugment, Time Stretch +- Reference only: Baseline + +## Files Included + +- `Sprint2_Augmentation_KD.ipynb` – main benchmarking notebook \ No newline at end of file