yigagilbert/stepaudio2-mini-luganda-english-s2st-lora

Step-Audio 2 Mini Luganda-to-English S2ST LoRA

This repository contains a LoRA adapter for stepfun-ai/Step-Audio-2-mini trained for Luganda speech input to English speech output. The adapter requires the base model and Step-Audio 2 token2wav assets for waveform synthesis.

Adapter repository: yigagilbert/stepaudio2-mini-luganda-english-s2st-lora

Intended use

Research and development for Luganda-to-English speech translation. Validate with native speakers before production use.

Training data

Configured for yigagilbert/luganda-english-cleaned-v1-split with columns: audio_lug, audio_eng, text_lug, text_eng, id, src_dur_s, tgt_dur_s, dur_ratio, src_speech_ratio, tgt_speech_ratio.

Evaluation

The table below summarizes the held-out validation evaluation used during development. All text metrics were computed on 200 validation examples. Speech metrics were computed on the aligned 197-example subset for which generated audio existed.

The merged full-model repository contains the same adapted weights as this adapter after LoRA merge, so it is expected to match these results aside from normal deterministic or runtime differences. Re-run evaluation directly on the merged repository before a strict release if exact reproducibility is required.

Text and Semantic Metrics

System	Loading Form	Count	BLEU higher	chrF higher	WER lower	COMET higher	BLASER ref higher	BLASER QE higher
Base Step-Audio-2-mini	Base only	200	0.012	5.152	10.702	0.386	1.713	2.164
Fine-tuned Step-Audio	Base + this LoRA adapter	200	32.530	54.535	0.574	0.717	3.762	3.723
Full merged fine-tuned model	Same adapted weights, merged	200	32.530*	54.535*	0.574*	0.717*	3.762*	3.723*
Cascade baseline	ASR + MT + TTS	200	36.778	57.971	0.521	0.737	3.839	3.776

* The merged full-model row reflects the adapter evaluation because the merged repository is produced by folding this LoRA adapter into the same base model.

Speech Metrics

System	Count	chrF higher	SpeechBERT P higher	SpeechBERT R higher	SpeechBERT F1 higher	MCD lower
Fine-tuned Step-Audio	197	54.582	0.644	0.648	0.645	629.718
Full merged fine-tuned model	197	54.582*	0.644*	0.648*	0.645*	629.718*
Cascade baseline	197	57.893	0.603	0.622	0.612	613.212

The unfine-tuned base model emitted no valid speech-token sequences in this 200-sample run, so SpeechBERTScore and MCD were not computed for it.

Interpretation

The LoRA adapter changes the base model from an unusable zero-shot system into a functioning Luganda-to-English speech translation model. The cascade remains stronger on text and semantic metrics, while the fine-tuned Step-Audio system is operationally simpler and scored higher on the WavLM-based SpeechBERTScore F1 proxy.

License

Adapter code and metadata are Apache-2.0. Check the dataset license separately before redistribution.