Stage 2 nonstandard speech fine-tune of openai/whisper-large-v3 on the CDLI Kenyan Swahili Nonstandard Speech dataset. Built on top of ElizabethMwangi/whisper-large-v3-swahili-afrivoice-cv, a Stage 1 checkpoint trained on AfriVoice (all 5 domains) interleaved with Common Voice Swahili.

Training Details

Stage 1 base: ElizabethMwangi/whisper-large-v3-swahili-afrivoice-cv (AfriVoice 5 domains + Common Voice)
Stage 2 dataset: cdli/kenyan_swahili_nonstandard_speech_v1.0 (849 examples)
Language token: sw
Full model training: encoder, decoder, and projection updated
SpecAugment: On
Learning rate: 5e-5 (polynomial decay, warmup 40 steps)
Max steps: 1000
Best checkpoint: step 550
Output dir: sw_nss_tune_whisper_v3_large_afrivoice_v1.2

Results on Kenyan Swahili Nonstandard Speech (test set, best checkpoint)

Overall, compared to unadapted baseline

Model	Overall WER	Avg WER
openai/whisper-large-v3 (no adaptation)	0.845	-
Stage 1 only (afrivoice-cv, no NSS tuning)	0.498	-
This model (adapted)	0.328	0.276

By severity