Practical overview
When it fits
Use StreamSpeech when you need to experiment with several speech tasks in one model project, especially simultaneous translation with intermediate recognition or translation output.
Who it is for
- Researchers and developers building or evaluating speech-processing workflows.
- Teams exploring streaming speech translation with intermediate text output.
Documented uses
- Transcribe speech in offline or streaming settings.
- Translate speech into text or translated speech.
- Generate speech from text, including incremental synthesis.
Requirements & limits
The repository is public and licensed under MIT. The README links a web GUI demo and downloadable model weights.
- The repository specifies Python 3.10, PyTorch 2.0.1, fairseq and SimulEval.
- The documented inference workflow requires model weights and test data in SimulEval format.
- The shown speech-to-speech inference command also references a Unit-based HiFi-GAN vocoder checkpoint and configuration.
- Listed model language pairs include French–English, Spanish–English and German–English.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Prepare a local inference setup
Prepare StreamSpeech dependencies, model files, configuration paths and test data for the repository's SimulEval inference workflow.
Before you start
- Python 3.10 and PyTorch 2.0.1
- fairseq and SimulEval
- A downloaded StreamSpeech model checkpoint
- Test data arranged in SimulEval format
Steps
Install fairseq and SimulEval in editable mode using the commands in the README.
Download a StreamSpeech model checkpoint for a listed language pair.
Replace the example repository path in the specified French–English configuration files with the local repository path.
Prepare a wav_list.txt of source-audio paths and a target.txt of reference text in the example format.
Expected outcome
The documented dependencies, model, configuration paths and test-data inputs are prepared for the next documented stage: inference with SimulEval.
Guide limitations
- These steps cover preparation only; they do not run inference.
- The configuration-path instructions specifically name the French–English config files.
- The README's shown speech-to-speech inference setup also requires a Unit-based HiFi-GAN vocoder checkpoint and configuration.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 14 October 2026
- Original website title
- ictnlp/StreamSpeech · Official homepage title · retained in its source language