speech-mcp 1.0.10

Speech MCP Server with command-line interface and Kokoro TTS support

Speech MCP

A Goose MCP extension for voice interaction with modern audio visualization.

Overview

Speech MCP provides a voice interface for Goose, allowing users to interact through speech rather than text. It includes:

• Real-time audio processing for speech recognition
• Local speech-to-text using faster-whisper (a faster implementation of OpenAI's Whisper model)
• High-quality text-to-speech with multiple voice options
• Modern PyQt-based UI with audio visualization
• Simple command-line interface for voice interaction

Features

• Modern UI: Sleek PyQt-based interface with audio visualization and dark theme
• Voice Input: Capture and transcribe user speech using faster-whisper
• Voice Output: Convert agent responses to speech with 54+ voice options
• Voice Persistence: Remembers your preferred voice between sessions
• Continuous Conversation: Automatically listen for user input after agent responses
• Silence Detection: Automatically stops recording when the user stops speaking
• Robust Error Handling: Graceful recovery from common failure modes

Installation

Option 1: Quick Install (One-Click)

Click the link below if you have Goose installed:

goose://extension?cmd=uvx&arg=speech-mcp&id=speech_mcp&name=Speech%20Interface&description=Voice%20interaction%20with%20audio%20visualization%20for%20Goose

Option 2: Using Goose CLI (recommended)

Start Goose with your extension enabled:

# If you installed via PyPI
goose session --with-extension "speech-mcp"

# Or if you want to use a local development version
goose session --with-extension "python -m speech_mcp"

Option 3: Manual setup in Goose

1. Run goose configure
2. Select "Add Extension" from the menu
3. Choose "Command-line Extension"
4. Enter a name (e.g., "Speech Interface")
5. For the command, enter: speech-mcp
6. Follow the prompts to complete the setup

Option 4: Manual Installation

1. Clone this repository
2. Install dependencies:

   uv pip install -e .
   

Dependencies

• Python 3.10+
• PyQt5 (for modern UI)
• PyAudio (for audio capture)
• faster-whisper (for speech-to-text)
• NumPy (for audio processing)
• Pydub (for audio processing)
• psutil (for process management)

Optional Dependencies

• Kokoro TTS: For high-quality text-to-speech with multiple voices
  • To install Kokoro, you can use pip with optional dependencies:

    pip install speech-mcp[kokoro]     # Basic Kokoro support with English
    pip install speech-mcp[ja]         # Add Japanese support
    pip install speech-mcp[zh]         # Add Chinese support
    pip install speech-mcp[all]        # All languages and features
    

  • Alternatively, run the installation script: python scripts/install_kokoro.py
  • See Kokoro TTS Guide for more information

Usage

To use this MCP with Goose, you can:

1. Start a conversation:

   user_input = start_conversation()
   

2. Reply to the user and get their response:

   user_response = reply("Your response text here")
   

Typical Workflow

# Start the conversation
user_input = start_conversation()

# Process the input and generate a response
# ...

# Reply to the user and get their response
follow_up = reply("Here's my response to your question.")

# Process the follow-up and reply again
reply("I understand your follow-up question. Here's my answer.")

UI Features

The new PyQt-based UI includes:

• Modern Dark Theme: Sleek, professional appearance
• Audio Visualization: Dynamic visualization of audio input
• Voice Selection: Choose from 54+ voice options
• Voice Persistence: Your voice preference is saved between sessions
• Animated Effects: Smooth animations and visual feedback
• Status Indicators: Clear indication of system state (ready, listening, processing)

Configuration

User preferences are stored in ~/.config/speech-mcp/config.json and include:

• Selected TTS voice
• TTS engine preference
• Voice speed
• Language code
• UI theme settings

You can also set preferences via environment variables, such as:

• SPEECH_MCP_TTS_VOICE - Set your preferred voice
• SPEECH_MCP_TTS_ENGINE - Set your preferred TTS engine

Troubleshooting

If you encounter issues with the extension freezing or not responding:

1. Check the logs: Look at the log files in src/speech_mcp/ for detailed error messages.
2. Reset the state: If the extension seems stuck, try deleting src/speech_mcp/speech_state.json or setting all states to false.
3. Use the direct command: Instead of uv run speech-mcp, use the installed package with speech-mcp directly.
4. Check audio devices: Ensure your microphone is properly configured and accessible to Python.
5. Verify dependencies: Make sure all required dependencies are installed correctly.

Recent Improvements

• Complete PyQt UI Migration: Replaced the old Tkinter UI with a modern PyQt implementation
• Code Refactoring: Split UI code into multiple components for better maintainability
• Process Management: Improved process lifecycle management with automatic recovery
• Voice Persistence: Added configuration system for saving user preferences
• Enhanced Visualization: Added dynamic audio visualization with animations
• Expanded Voice Options: Updated to support 54 different voice models
• Improved Error Handling: Better recovery from common failure modes

Technical Details

Speech-to-Text

The MCP uses faster-whisper for speech recognition:

• Uses the "base" model for a good balance of accuracy and speed
• Processes audio locally without sending data to external services
• Automatically detects when the user has finished speaking
• Provides improved performance over the original Whisper implementation

Text-to-Speech

The MCP supports multiple text-to-speech engines:

Default: pyttsx3

• Uses system voices available on your computer
• Works out of the box without additional setup
• Limited voice quality and customization

Optional: Kokoro TTS

• High-quality neural text-to-speech with multiple voices
• Lightweight model (82M parameters) that runs efficiently on CPU
• Multiple voice styles and languages
• To install: python scripts/install_kokoro.py

Note about Voice Models: The voice models are .pt files (PyTorch models) that are loaded by Kokoro. Each voice model is approximately 523 KB in size and is automatically downloaded when needed.

Voice Persistence: The selected voice is automatically saved to a configuration file (~/.config/speech-mcp/config.json) and will be remembered between sessions. This allows users to set their preferred voice once and have it used consistently.

Available Kokoro Voices

American Female Voices

• af_alloy, af_aoede, af_bella, af_heart, af_jessica, af_kore, af_nicole, af_nova, af_river, af_sarah, af_sky

American Male Voices

• am_adam, am_echo, am_eric, am_fenrir, am_liam, am_michael, am_onyx, am_puck, am_santa

British Female Voices

• bf_alice, bf_emma, bf_isabella, bf_lily

British Male Voices

• bm_daniel, bm_fable, bm_george, bm_lewis

Other English Voices

• ef_dora, em_alex, em_santa

Other Languages

• French: ff_siwis
• Hindi: hf_alpha, hf_beta, hm_omega, hm_psi
• Italian: if_sara, im_nicola
• Japanese: jf_alpha, jf_gongitsune, jf_nezumi, jf_tebukuro, jm_kumo
• Portuguese: pf_dora, pm_alex, pm_santa
• Chinese: zf_xiaobei, zf_xiaoni, zf_xiaoxiao, zf_xiaoyi, zm_yunjian, zm_yunxi, zm_yunxia, zm_yunyang

License

MIT License