Hugging Face's logo

Spaces:
Agents-MCP-Hackathon
/
ModalTranscriberMCP
Running

App Files Community
ModalTranscriberMCP / README.md
richard-su's picture
richard-su
Upload README.md with huggingface_hub
4bbc337 verified
preview code
|
raw
history blame contribute delete
3.6 kB
metadata
title: Modal Transcriber MCP
emoji: 🎙️
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
license: mit
tag: mcp-server-track

🎙️ Modal Transcriber MCP

A powerful audio transcription system integrating Gradio UI, FastMCP Tools, and Modal cloud computing with intelligent speaker identification.

✨ Key Features

  • 🎵 Multi-platform Audio Download: Support for Apple Podcasts, XiaoYuZhou, and other podcast platforms
  • 🚀 High-performance Transcription: Based on OpenAI Whisper with multiple model support (turbo, large-v3, etc.)
  • 🎤 Intelligent Speaker Identification: Using pyannote.audio for speaker separation and embedding clustering
  • ⚡ Distributed Processing: Support for large file concurrent chunk processing, significantly improving processing speed
  • 🔧 FastMCP Tools: Complete MCP (Model Context Protocol) tool integration
  • ☁️ Modal Deployment: Support for both local and cloud deployment modes

🎯 Core Advantages

🧠 Intelligent Audio Segmentation

  • Silence Detection Segmentation: Automatically identify silent segments in audio for intelligent chunking
  • Fallback Mechanism: Long audio automatically degrades to time-based segmentation, ensuring processing efficiency
  • Concurrent Processing: Multiple chunks processed simultaneously, dramatically improving transcription speed

🎤 Advanced Speaker Identification

  • Embedding Clustering: Using deep learning embeddings for speaker consistency identification
  • Cross-chunk Unification: Solving speaker label inconsistency issues in distributed processing
  • Quality Filtering: Automatically filter low-quality segments to improve output accuracy

🔧 Developer Friendly

  • MCP Protocol Support: Complete tool invocation interface
  • REST API: Standardized API interface
  • Gradio UI: Intuitive web interface
  • Test Coverage: 29 unit tests and integration tests

🚀 Quick Start

Local Setup

  1. Clone Repository
git clone https://huggingface.co/spaces/Agents-MCP-Hackathon/ModalTranscriberMCP
cd ModalTranscriberMCP
  1. Install Dependencies
pip install -r requirements.txt
  1. Configure Hugging Face Token (Optional, for speaker identification)
# Create .env file
echo "HF_TOKEN=your_huggingface_token_here" > .env
  1. Start Application
python app.py

Usage Instructions

  1. Upload audio file or Input podcast URL
  2. Select transcription options:
    • Model size: turbo (recommended) / large-v3
    • Output format: SRT / TXT
    • Enable speaker identification
  3. Start transcription, the system will automatically process and generate results

🛠️ Technical Architecture

  • Frontend: Gradio 4.44.0
  • Backend: FastAPI + FastMCP
  • Transcription Engine: OpenAI Whisper
  • Speaker Identification: pyannote.audio
  • Cloud Computing: Modal.com
  • Audio Processing: FFmpeg

📊 Performance Metrics

  • Processing Speed: Support for 30x real-time transcription speed
  • Concurrency: Up to 10 chunks processed simultaneously
  • Accuracy: Chinese accuracy >95%
  • Supported Formats: MP3, WAV, M4A, FLAC, etc.

🤝 Contributing

Issues and Pull Requests are welcome!

📜 License

MIT License

🔗 Related Links

  • Project Documentation: See docs/ directory in the repository
  • Test Coverage: 29 test cases ensuring functional stability
  • Modal Deployment: Support for cloud high-performance processing

Last updated: 2025-06-11