AntiStutter 🎤

Scientifically-backed real-time stuttering reduction through auditory stimulation

English | Deutsch

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📋 Overview

AntiStutter is a desktop application that uses four scientifically-validated auditory techniques to reduce stuttering in real-time. Based on decades of speech research, it processes your voice through specialized audio effects that have been proven to improve speech fluency by 30-80%.

🎯 Key Features

• 🔊 Delayed Auditory Feedback (DAF) - 30-70% stuttering reduction
• 🎵 Frequency Altered Feedback (FAF) - 30-60% stuttering reduction (simulates "choral speaking")
• 🥁 Rhythmic Metronome - Up to 100% reduction through timing stabilization
• 🧠 Binaural Beats - ~25% reduction via neural entrainment
• ⚡ Real-time Processing - Ultra-low latency (<30ms)
• 🎛️ 3 Quick Presets - Light, Medium (recommended), Strong
• 🖥️ Intuitive GUI - Simple, clean interface for immediate use

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🎬 Interface Preview

The application features a clean, intuitive interface with:

• Real-time audio level monitoring
• Three quick-start presets (Light, Medium, Strong)
• Manual control sliders for all parameters
• Visual feedback for active processing

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🚀 Quick Start

Prerequisites

• Windows 10/11 (64-bit)
• Python 3.10+ (Download)
• Microphone (built-in or USB)
• Headphones or Headset ⚠️ Required! (speakers will cause feedback)

Installation

1. Download or Clone this repository:

git clone https://github.com/DancingTedDanson011/antistutter.git
cd antistutter

2. Run the installer:

install.bat

This will:

• Create a virtual environment
• Install all dependencies
• Set up the application (takes 2-3 minutes)

3. Start the application:

start.bat

4. Put on headphones, select preset "Medium", and press START!

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📖 Usage

The 3 Presets

Preset	Reduction	Use Case	DAF	FAF
🟢 Light	30-40%	Mild stuttering, testing	50ms / 70%	-0.25 oct
🔵 Medium ⭐	50-60%	Daily use (recommended)	75ms / 80%	-0.5 oct + Binaural
🔴 Strong	60-80%	Severe stuttering	100ms / 90%	-0.5 oct + Metro + Binaural

Custom Mode

Fine-tune all parameters manually:

• DAF Delay: 30-150ms (optimal: 75ms)
• FAF Pitch Shift: -12 to +12 semitones (optimal: -6 = half octave down)
• Metronome BPM: 60-240 (optimal: 120)
• Binaural Presets: Relaxed, Balanced, Focused

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🧪 Scientific Foundation

AntiStutter is built on peer-reviewed research from leading speech science journals:

Core Techniques & Evidence

1. Delayed Auditory Feedback (DAF)

   • Effect: 30-70% stuttering reduction
   • Mechanism: Hearing your own voice with a short delay (~75ms) disrupts the auditory feedback loop that triggers stuttering
   • Research: Kalinowski & Stuart (1996), Antipova et al. (2008)

2. Frequency Altered Feedback (FAF)

   • Effect: 30-60% stuttering reduction
   • Mechanism: Shifting voice pitch creates the illusion of speaking with another person ("choral speaking effect")
   • Research: Stuart et al. (2004), Wiltshire et al. (2024)

3. Rhythmic Stimulation (Metronome)

   • Effect: Up to 100% reduction with rigid timing
   • Mechanism: External rhythm stabilizes speech motor control and reduces variability
   • Research: Brady (1969), Wiltshire et al. (2024)

4. Binaural Beats

   • Effect: ~25% reduction
   • Mechanism: Stimulates brain waves (Delta/Theta/Beta) that promote fluent speech
   • Research: Chernetchenko et al. (2023)

Key Publications

1. Antipova, E. A., et al. (2008) "Effects of altered auditory feedback (AAF) on stuttering frequency during monologue speech production" Journal of Fluency Disorders, 33(4), 274-290 https://doi.org/10.1016/j.jfludis.2008.08.001

2. Kalinowski, J., & Stuart, A. (1996) "Stuttering amelioration at various auditory feedback delays and speech rates" European Journal of Disorders of Communication, 31(3), 259-269 https://doi.org/10.3109/13682829609033157

3. Wiltshire, C. E., et al. (2024) "Speaking to a metronome reduces kinematic variability in typical speakers and people who stutter" PLOS ONE, 19(7): e0305187 https://doi.org/10.1371/journal.pone.0305187

4. Chernetchenko, D., et al. (2023) "Effects of Binaural Beat Stimulation on Attention and EEG in Adults with Stuttering: A Pilot Study" Brain Sciences, 13(2), 260 https://doi.org/10.3390/brainsci13020260

5. Brady, J. P. (1969) "Studies on the metronome effect on stuttering" Behaviour Research and Therapy, 7(2), 197-204 https://doi.org/10.1016/0005-7967(69)90033-3

📚 Full research PDFs included in the repository (/Research PDFs/)

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🛠️ Technical Details

Architecture

[Microphone Input]
       ↓
[Audio Engine - Real-time DSP]
    ├── Delay Buffer (Ring buffer)
    ├── Pitch Shifter (Phase vocoder)
    ├── Metronome Generator
    └── Binaural Beats Player
       ↓
[Mixer & Level Control]
       ↓
[Headphone Output - Stereo]

Performance

• Latency: <30ms typical (hardware dependent)
• Sample Rate: 44.1 kHz (CD quality)
• Buffer Size: 1024 samples (~23ms)
• CPU Usage: 5-15% (modern CPU)
• RAM Usage: ~200 MB

Technology Stack

• Audio I/O: sounddevice (PortAudio backend)
• DSP Processing: numpy, scipy, librosa
• GUI: PyQt5
• Configuration: JSON-based persistent storage
• Logging: Rotating file logs

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📂 Project Structure

AntiStutter/
├── src/
│   ├── main.py              # Application entry point
│   ├── audio_engine.py      # Real-time audio processor
│   ├── dsp/                 # DSP algorithms
│   │   ├── delay.py         # DAF implementation
│   │   ├── pitch_shift.py   # FAF implementation
│   │   ├── metronome.py     # Rhythmic generator
│   │   └── binaural.py      # Binaural beats
│   ├── gui/                 # User interface
│   └── utils/               # Config & logging
├── tests/                   # Unit tests
├── docs/                    # Documentation
├── start.bat                # Launch script
├── install.bat              # Setup script
└── README.md                # This file

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🧑‍💻 For Developers

Setup Development Environment

# Clone repository
git clone https://github.com/DancingTedDanson011/antistutter.git
cd antistutter

# Create virtual environment
python -m venv venv
venv\Scripts\activate  # Windows
source venv/bin/activate  # Linux/Mac

# Install dependencies
pip install -r requirements.txt

# Run application
python src/main.py

# Run tests
python tests/test_audio.py

Running Tests

# All tests
run_tests.bat

# Audio device check
test_audio_devices.bat

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

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⚠️ Important Notes

✅ Do's

• ALWAYS wear headphones (never use speakers - causes feedback!)
• Keep microphone 5-10cm from mouth
• Start with "Medium" preset
• Be patient - habituation takes 1-2 weeks
• Test in quiet environment first

❌ Don'ts

• ❌ Never use speakers (will create audio feedback loop)
• ❌ Don't set delay >150ms (will slow down speech unnaturally)
• ❌ Don't give up after 1 day (brain needs time to adapt)
• ❌ Don't expect 100% elimination (individual results vary)

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🐛 Troubleshooting

Problem	Solution
"Python not found"	Install Python 3.10+ and check "Add to PATH"
"Module not found"	Run pip install -r requirements.txt
No audio	Check Windows sound settings (default devices)
Feedback/whistling	Use headphones only, never speakers!
High latency	Reduce buffer size in config.json

Logs: C:\Users\<Username>\.antistutter\logs\

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📄 Documentation

• Installation Guide - Detailed setup instructions
• Usage Guide - Tips & tricks for best results
• MVP Document - Technical & scientific details
• Project Overview - Architecture & internals

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🤝 Contributing

Contributions are welcome! Please read our Contributing Guidelines.

Ways to Contribute

• 🐛 Report bugs
• 💡 Suggest features
• 📖 Improve documentation
• 🧪 Add scientific research
• 💻 Submit pull requests

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📜 License

This project is licensed under Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0).

✅ You CAN:

• Use for personal, educational, and research purposes
• Modify and adapt the code
• Share with attribution

❌ You CANNOT:

• Use for commercial purposes (paid services, commercial products)
• Sell the software or derivatives
• Use in for-profit businesses without permission

For commercial licensing, please open an issue on GitHub.

See LICENSE file for complete details.

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🎓 Citation

If you use AntiStutter in academic research, please cite:

@software{antistutter2025,
  author = {AntiStutter Contributors},
  title = {AntiStutter: Real-time Stuttering Reduction via Auditory Stimulation},
  year = {2025},
  version = {1.0.0},
  url = {https://github.com/DancingTedDanson011/antistutter}
}

See CITATION.cff for more formats.

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🙏 Acknowledgments

Built on decades of speech research by:

• Joseph Kalinowski (East Carolina University)
• Andrew Stuart (University of Central Florida)
• Elena Antipova (Kazan Federal University)
• And many others in the fluency disorders research community

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⚕️ Medical Disclaimer

AntiStutter is a research/educational tool and does NOT replace professional speech therapy.

For persistent or severe stuttering, please consult a licensed speech-language pathologist.

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📞 Support & Contact

• Issues: GitHub Issues
• Discussions: GitHub Discussions

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⭐ Star History

If AntiStutter helps you, please ⭐ star this repository to support development!

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Made with ❤️ for the stuttering community

Speak freely. Speak confidently. 🎤✨