audio-scribe 0.1.6

A command-line tool for audio transcription with Whisper and Pyannote.

Audio Scribe

A Command-Line Tool for Audio Transcription and Speaker Diarization Using OpenAI Whisper and Pyannote

Support the Project ☕

If you find Audio Scribe helpful, consider supporting the project with a coffee!
Your contribution helps maintain the project and develop new features.

Overview

Audio Scribe is a command-line tool that transcribes audio files with speaker diarization. Leveraging OpenAI Whisper for transcription and Pyannote Audio for speaker diarization, this solution converts audio into segmented text files, identifying each speaker turn. Key features include:

• Progress Bar & Resource Monitoring: See real-time CPU, memory, and GPU usage with a live progress bar.
• Speaker Diarization: Automatically separates speaker turns using Pyannote’s state-of-the-art models.
• Tab-Completion for File Paths: Easily navigate your file system when prompted for the audio path.
• Secure Token Storage: Encrypts and stores your Hugging Face token for private model downloads.
• Customizable Whisper Models: Default to base.en, or specify tiny, small, medium, large, etc.

This repository is licensed under the Apache License 2.0.

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Table of Contents

• Audio Scribe
  • A Command-Line Tool for Audio Transcription and Speaker Diarization Using OpenAI Whisper and Pyannote
  • Support the Project ☕
  • Overview
  • Table of Contents
  • Features
  • Installation
    • Installing from PyPI
    • Installing from GitHub
  • Quick Start
  • Usage
  • Dependencies
    • Sample requirements.txt
  • Troubleshooting
    • IndexError: list index out of range
      • Option 1: System-level Installation (requires sudo access)
      • Option 2: Conda-only Installation (no sudo required)
  • Contributing
  • License

Features

• Whisper Transcription
  Utilizes OpenAI Whisper to convert speech to text in multiple languages.
• Pyannote Speaker Diarization
  Identifies different speakers and segments your audio output accordingly.
• Progress Bar & Resource Usage
  Displays a live progress bar with CPU, memory, and GPU stats through alive-progress, psutil, and GPUtil.
• Tab-Completion
  Press Tab to autocomplete file paths on Unix-like systems (and on Windows with pyreadline3).
• Secure Token Storage
  Saves your Hugging Face token via cryptography for model downloads (e.g., pyannote/speaker-diarization-3.1).
• Configurable Models
  Default is base.en but you can specify any other Whisper model using --whisper-model.

Installation

Installing from PyPI

Audio Scribe is available on PyPI. You can install it with:

pip install audio-scribe

After installation, the audio-scribe command should be available in your terminal (depending on how your PATH is configured). If you prefer to run via Python module, you can also do:

python -m audio-scribe --audio path/to/yourfile.wav

Installing from GitHub

To install the latest development version directly from GitHub:

git clone https://gitlab.genomicops.cloud/innovation-hub/audio-scribe.git
cd audio-scribe
pip install -r requirements.txt

This approach is particularly useful if you want the newest changes or plan to contribute.

Quick Start

1. Obtain a Hugging Face Token

   • Create a token at Hugging Face Settings.
   • Accept the model conditions for pyannote/segmentation-3.0 and pyannote/speaker-diarization-3.1.

2. Run the Command-Line Tool

   audio-scribe --audio path/to/audio.wav
   

   On the first run, you’ll be prompted for your Hugging Face token if you haven’t stored one yet.

3. Watch the Progress Bar

   • The tool displays a progress bar for each diarized speaker turn, along with real-time CPU, GPU, and memory usage.

Usage

Below is a summary of the main command-line options:

usage: audio-scribe [options]

Audio Transcription (Audio Scribe) Pipeline using Whisper + Pyannote, with optional progress bar.

optional arguments:
  --audio PATH           Path to the audio file to transcribe.
  --token TOKEN          HuggingFace API token. Overrides any saved token.
  --output PATH          Path to the output directory for transcripts and temporary files.
  --delete-token         Delete any stored Hugging Face token and exit.
  --show-warnings        Enable user warnings (e.g., from pyannote.audio). Disabled by default.
  --whisper-model MODEL  Specify the Whisper model to use (default: 'base.en').

Examples:

• Basic Transcription

  audio-scribe --audio meeting.wav
  

• Specify a Different Whisper Model

  audio-scribe --audio webinar.mp3 --whisper-model small
  

• Delete a Stored Token

  audio-scribe --delete-token
  

• Show Internal Warnings

  audio-scribe --audio session.wav --show-warnings
  

• Tab-Completion

  audio-scribe
  # When prompted for an audio file path, press Tab to autocomplete
  

Dependencies

Core Libraries

• Python 3.8+
• PyTorch
• openai-whisper
• pyannote.audio
• pytorch-lightning
• cryptography
• keyring

Optional for Extended Functionality

• alive-progress – Real-time progress bar
• psutil – CPU/memory usage
• GPUtil – GPU usage
• pyreadline3 (for Windows tab-completion)

Sample requirements.txt

Below is a typical requirements.txt you can place in your repository:

torch>=1.9
openai-whisper
pyannote.audio
pytorch-lightning
cryptography
keyring
alive-progress
psutil
GPUtil
pyreadline3; sys_platform == "win32"

Note:

• pyreadline3 is appended with a PEP 508 marker (; sys_platform == "win32") so it only installs on Windows.
• For GPU support, ensure you install a compatible PyTorch version with CUDA.

Troubleshooting

IndexError: list index out of range

Symptom

You encounter the following error when running audio-scribe or importing pyannote.audio:

IndexError: list index out of range
  File ".../pyannote/audio/core/io.py", line 214, in __init__
    backend = "soundfile" if "soundfile" in backends else backends[0]

This occurs when pyannote.audio is unable to detect any supported audio backend. Most commonly, the soundfile module is missing or its dependency libsndfile is not properly installed.

Solution

You have two ways to resolve this issue:

Option 1: System-level Installation (requires sudo access)

Install the system-level audio backend library:

sudo apt-get update
sudo apt-get install libsndfile1

Then reinstall the soundfile Python package inside your environment:

# If using conda
conda activate your-environment-name
pip uninstall soundfile -y
pip install soundfile

# If using pip/virtualenv
source your-venv/bin/activate  # or equivalent activation command
pip uninstall soundfile -y
pip install soundfile

Option 2: Conda-only Installation (no sudo required)

Inside your Conda environment:

conda activate your-environment-name
conda install -c conda-forge libsndfile

Then ensure Python uses the correct bindings:

pip uninstall soundfile -y
pip install soundfile

Verification

Test that audio backends are now available:

python -c "import soundfile as sf; print(sf.available_formats())"

Expected output:

{'WAV': 'Microsoft WAV format (little endian)', 'FLAC': 'FLAC format', ...}

Then re-run audio-scribe:

audio-scribe --audio path/to/your/audio.wav

The tool should now initialize without error.

Contributing

We welcome contributions to Audio Scribe!

1. Fork the repository and clone your fork.
2. Create a new branch for your feature or bugfix.
3. Implement your changes, ensuring code is well-documented and follows best practices.
4. Open a pull request, detailing the changes you’ve made.

Please read any available guidelines or templates in our repository (such as CONTRIBUTING.md or CODE_OF_CONDUCT.md) before submitting.

License

This project is licensed under the Apache License 2.0.

Copyright 2025 Gurasis Osahan

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

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Thank you for using Audio Scribe!
For questions or feedback, please open a GitHub issue or contact the maintainers.