Practical overview
When it fits
Use Reverb when you need code-level access to Rev’s speech-recognition or diarization workflows and can manage the Python or Docker setup and model access.
Who it is for
- Developers adding speech-to-text inference to Python workflows
- Teams evaluating speech-recognition or speaker-diarization models
- Practitioners who want to run Rev’s ASR or diarization code through documented Python or Docker workflows
Documented uses
- Transcribe audio files and save results to a chosen output directory.
- Adjust transcription verbatimicity or decoding mode.
- Return transcription in CTM format instead of text.
- Run or evaluate speaker-diarization workflows based on Pyannote.
Requirements & limits
The repository is public and lists an Apache-2.0 code license. The README requires Hugging Face access-token setup for its getting-started instructions; model licenses are separate and must be checked on Hugging Face.
- Python 3.10 or later is required for the Python setup.
- The README warns that another WeNet installation in the same environment may cause conflicts.
- Model weights are distinct from the Apache-2.0-licensed repository code; check the relevant model page for model licensing.
- The repository documents Docker for running ASR and/or diarization, with additional steps potentially required for NVIDIA GPU use.
- The README points to a separate self-hosted release for larger-scale deployment and says that approach supports deployment without internet connectivity or cloud dependencies.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Set up Reverb for Python-based ASR
Install the Reverb package and prepare the documented prerequisites for using its ASR workflow.
Before you start
- Python 3.10 or later
- Hugging Face access token and CLI login
- Git LFS installed
- No other WeNet installation in the same Python environment
Steps
Set up Hugging Face CLI access with an access token.
Run the command below in a terminal.
git lfs installFrom the repository, run the command below in the Python environment.
pip install .
Expected outcome
The `reverb` package is installed and the README’s stated setup prerequisites are in place for proceeding to the ASR usage instructions.
Guide limitations
- This setup sequence does not itself run transcription.
- Model licensing is separate from the repository code license and should be checked on the relevant Hugging Face model page.
Build the Reverb Docker image
Prepare the documented Docker image for running ASR and/or diarization.
Before you start
- Docker installed
- Hugging Face access token
Steps
Set up a Hugging Face access token.
From the repository, build the image with the command below.
docker build -t reverb . --build-arg HUGGINGFACE_ACCESS_TOKEN=${YOUR_HUGGINGFACE_ACCESS_TOKEN}
Expected outcome
The README provides a Docker image build step for the Reverb workflows.
Guide limitations
- Running on an NVIDIA GPU may require additional steps.
- The README’s separate container-run command starts a Bash entrypoint; it does not document a complete inference command inside the container.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 14 October 2026
- Original website title
- revdotcom/reverb · Official homepage title · retained in its source language