local-input-select-stt

Pipecat Audio Transcription Example 🚀🎙️

Welcome to the Pipecat Audio Transcription Example!

This project showcases how to integrate the awesome pipecat library with a neat textual interface (powered by Textual) to select audio devices, perform real-time speech-to-text (STT) transcription using Whisper.

Note: Although the script allows you to select both input and output audio devices, this example only utilizes the audio input for transcription.

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🎉 Features

• Interactive Audio Device Selection:
  Choose your preferred audio input device using a cool, textual UI.
• State-of-the-Art Transcription:
  Leverage Whisper's large model (running on CUDA) for high-quality, real-time STT.
• Live Transcription Logging:
  Watch your spoken words transform into text on your console instantly.
• Easy Setup:
  Everything you need is in the requirements.txt.

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🎥 Demo

Get a quick glimpse of the app in action!
(Don't worry – I'll be adding a GIF demo here soon!)

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🔧 Installation

Install dependencies:

uv sync

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🚀 Usage

Run the main script:

uv run bot.py

When the app launches, you'll see a textual interface that lets you select your audio input device. Once selected, the app will begin capturing audio, transcribing it using Whisper.

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⚙️ How It Works

1. LocalAudioTransport:
   Captures audio from your chosen input device.
2. WhisperSTTService:
   Processes the audio stream using Whisper's large model for speech-to-text conversion.
3. TranscriptionLogger:
   Logs the transcribed text to the console as soon as it's processed.

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📦 Dependencies

The project relies on:

• pipecat – For building the audio processing pipeline.
• Textual – For the interactive terminal UI.
• Whisper – For state-of-the-art STT transcription.

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Example improvements:

I plan to improve this example with local LLM calls and audio output.