Kiragu/whisper-small-kikuyu-v4

Whisper Small — Kikuyu (Gikuyu) V4

Fine-tuned openai/whisper-small for Kikuyu (Gikuyu) automatic speech recognition.

Model Details

• Base model: openai/whisper-small (244M params)
• Fine-tuning: LoRA r=32, alpha=64, targets: q/k/v/out_proj/fc1/fc2
• Dataset: google/WaxalNLP kik_tts (~1,226 train samples, ~6.5 hours)
• Diacritics: Preserved (canonical ĩ, ũ)
• Training: 1,500 steps, cosine LR schedule, SpecAugment, label smoothing 0.1

Results

Split	WER	CER
Eval	78.2%	40.4%
Test	83.6%	47.8%

Usage

from transformers import WhisperProcessor, WhisperForConditionalGeneration

processor = WhisperProcessor.from_pretrained("Kiragu/whisper-small-kikuyu-v4")
model = WhisperForConditionalGeneration.from_pretrained("Kiragu/whisper-small-kikuyu-v4")

input_features = processor(audio_array, sampling_rate=16000, return_tensors="pt").input_features
predicted_ids = model.generate(input_features)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]

Limitations

• WER is still high (78-84%) — experimental model
• Only ~6.5 hours of training data
• Short phrases work better than long sentences
• May hallucinate/repeat on longer audio

Part of Sauti AI

This model is part of Sauti AI, a decentralized vocal data collection platform for underrepresented languages.