---
language:
- sw
tags:
- whisper
- automatic-speech-recognition
- swahili
- nonstandard-speech
- kenya
- low-resource
datasets:
- ElizabethMwangi/swahili_afrivoice_all_domains_v0.1
- cdli/kenyan_swahili_nonstandard_speech_v1.0
base_model: ElizabethMwangi/whisper-large-v3-swahili-afrivoice-5domains
license: apache-2.0
---

# Whisper Large V3 — Swahili NSS (AfriVoice 5 Domains)

Stage 2 nonstandard speech fine-tune of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the CDLI Kenyan Swahili Nonstandard Speech dataset. Built on top of [ElizabethMwangi/whisper-large-v3-swahili-afrivoice-5domains](https://huggingface.co/ElizabethMwangi/whisper-large-v3-swahili-afrivoice-5domains), a Stage 1 checkpoint trained on AfriVoice Swahili across all 5 domains (389,599 utterances), best step 600.

## Training Details

- **Stage 1 base:** ElizabethMwangi/whisper-large-v3-swahili-afrivoice-5domains (AfriVoice 5 domains, 389,599 utterances)
- **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 650
- **Output dir:** sw_nss_tune_whisper_v3_large_afrivoice_v1.3

## 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-5domains, no NSS tuning) | 0.434 | - |
| This model (adapted) | 0.329 | 0.279 |

| Metric | Value |
|--------|-------|
| Overall WER | 0.329 |
| Overall CER | 0.171 |
| Avg WER | 0.279 |
| Avg CER | 0.128 |
| Meaning preservation | 75.7% |

**By severity**

| Severity | WER | CER |
|----------|-----|-----|
| Mild | 0.21 | 0.09 |
| Moderate | 0.25 | 0.11 |
| Severe | 0.35 | 0.16 |