CDLI Qwen3-ASR Luganda Atypical Speech Prompt Fine-tune
Selected checkpoint: checkpoint-1000.
Prompt Setup
- Prompt mode:
metadata - Method note: This is a metadata-conditioned/oracle prompt experiment. The prompt uses speaker severity, disorder type, and etiology from
speaker_metadata.csv; compare it separately from deployment baselines. - WER framing: this notebook does not ask the model to remove repetitions, clean disfluencies, summarize, or normalize grammar.
Test Metrics
- Normalized WER: 0.632689
- Normalized CER: 0.340070
- Avg capped WER: 0.491120
- Avg capped CER: 0.229225
Training Setup
- Dataset:
cdli/ugandan_luganda_nonstandard_speech_v1.0 - Splits: cleaned TSVs matched by
audio_id - Base model:
KasuleTrevor/cdli-qwen3-asr-lg-typical-1p7b-base-finetune - LR:
0.0001 - Scheduler:
constant_with_warmup - Epochs:
3 - Train mode:
full - Seed:
42
Metadata Prompt Template
Speaker speech disorder type, speech impairment severity, and etiology are inserted from metadata. The prompt then instructs exact Luganda transcription while preserving repetitions, disfluencies, false starts, and partial words.