The primary goal of this project is to design and implement an intent recognition system capable of accurately understanding user intents conveyed through natural language input. The system should be able to classify user queries or commands into predefined categories or intents, enabling effective interaction between users and the system.
- Defined a set of intents relevant to the domain of application.
- Collected and pre-processed a diverse dataset of user queries or commands annotated with their corresponding intents.
- Tokenized and padded the input text data.
- Encoded the labels (intents) into numerical values.
- Built and trained a neural network model using TensorFlow.
- Evaluated the model to ensure it meets the specified performance metrics.
The trained intent recognition model is capable of classifying user queries into predefined intents with high accuracy.
- Expand the dataset to include more diverse and complex queries.
- Fine-tune the model with hyperparameter optimization.
- Integrate the model into a real-time application for deployment.