Reverb

Open-source inference code for speech recognition and speaker segmentation models.

CommonProductProgrammingSpeech RecognitionSpeaker Segmentation

Reverb is an open-source inference codebase for speech recognition and speaker segmentation models, utilizing the WeNet framework for ASR and the Pyannote framework for speaker segmentation. It offers detailed model descriptions and allows users to download models from Hugging Face. Reverb aims to provide developers and researchers with high-quality tools for various speech processing tasks.

Speech recognition code based on the WeNet framework
Speaker segmentation code based on the Pyannote framework
Provides WER and WDER results for long-form speech recognition and speaker segmentation
Supports model downloads via Hugging Face Hub
Offers Docker images to simplify deployment
Compatible with NVIDIA GPUs for enhanced performance
Includes detailed installation and usage instructions

\The target audience primarily includes researchers
developers
and corporate users in the fields of speech recognition and speaker segmentation. Reverb provides high-quality speech processing tools suitable for tasks such as meeting transcription and phone call analysis.\

Automatic speech recognition and speaker segmentation for meeting documentation
Voice content analysis for customer service call recordings
Transcription and speaker identification for courtroom records

1. Ensure that Git Large File Storage (LFS) is installed on your system.
2. Use HUGGINGFACE_ACCESS_TOKEN to download models from the Hugging Face Hub.
3. Clone the Reverb code repository to your local machine.
4. Set up and activate a virtual environment.
5. At the root directory of the code repository

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Monthly Visits

488643166

Bounce Rate

37.28%

Page per Visit

5.7

Visit Duration

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