msingiai/sauti-asr-track-b-preview
This repo stages the current Sauti ASR Track B research preview. The checkpoint
is a fine-tuned derivative of omniASR_LLM_300M_v2 and is intended for research
use, inspection, and side-by-side evaluation against the main Track A release.
The public-facing training-data summary omits restricted internal sources.
Release Status
- Release type: research preview
- Best saved checkpoint:
step_250
- Best validation WER:
15.13%
- Validation split:
dev
- Validation samples:
1000
- Source run:
track_b_omnilingual_llm_300m_v2_tuned_v1
Important Packaging Note
- The
model/ directory in this repo is an Omnilingual / fairseq2 checkpoint
bundle, not a transformers checkpoint.
- This repo is not intended for hosted Hugging Face inference endpoints.
- Use it with the Omnilingual ASR codebase and a local asset-card file.
Training Data
The current preview was trained from the repo Track B Swahili dataset mix:
| Dataset | License | Notes |
|---|
mozilla-common-voice | Common Voice (CC0) | Used in repo Track B pipeline |
google-fleurs | FLEURS (CC-BY-4.0) | Used in repo Track B pipeline |
alffa-swahili-news | ALFFA / OpenSLR (MIT) | Used in repo Track B pipeline |
keystats-swahili-asr-data | KeyStats (Apache-2.0) | Used in repo Track B pipeline |
Current Strengths
- More useful than the current Track A path on the long ANC consultation spot
check used in this repo.
- Better suited to conversational Swahili and mixed clinical speech than the
current Track A service output.
Current Limitations
- Not benchmark-leading yet relative to the best Track A held-out result.
- Long-form decoding in the repo still uses simple chunk-and-stitch inference.
- Clinical conversations still show many phonetic substitutions and
code-switching errors.
- The checkpoint is packaged for research tooling rather than turnkey hosted
inference.
Local Usage
- Download or clone this repo locally.
- Copy
sauti_asr_track_b_preview.asset.yaml into an Omnilingual ASR checkout.
- Replace the placeholder checkpoint path with the absolute path to the local
model/ directory from this repo.
- Load the checkpoint via
ASRInferencePipeline(model_card="sauti_asr_track_b_preview").
Asset Card Template
The staged folder includes sauti_asr_track_b_preview.asset.yaml with:
model_family: wav2vec2_llama
model_arch: 300m_v2
tokenizer_ref: omniASR_tokenizer_written_v2
Source Repository
The training, evaluation, and serving code lives in:
Responsible Use
This research preview transcribes speech and may be inaccurate on sensitive
audio, including clinical conversations. Users are responsible for consent,
privacy handling, and downstream review before any real-world use.