VibeVoice ASR — Kazakh

Model Description

This is VibeVoice ASR fine-tuned on the Kazakh language using the ISSAI KSC2 Structured dataset (~1,200 hours of diverse Kazakh speech). Fine-tuning was performed using LoRA (Low-Rank Adaptation) and the weights were merged into the base model for efficient inference. Model demonstrated 22% WER on test set of ISSAI KSC2.

The base VibeVoice ASR model had no prior Kazakh knowledge. This fine-tuned version produces punctuated and capitalized Kazakh transcriptions.

Training Dataset

InflexionLab/ISSAI-KSC2-Structured — an enhanced version of the ISSAI KSC2 corpus with punctuation and capitalization restored using Gemma 27B. Covers 6 domains: TV News, Crowdsourced, Parliament, Talkshow, Podcasts, and Radio.

Evaluation Results

Evaluated on the KSC2 Test split (9,351 samples) and farabi-lab/kazakh-stt 30K samples. Farabi-Lab dataset was not included in training.

Dataset	WER	CER
ISSAI_KSC2	~22%	~9.6%
farabi-lab/kazakh-stt	17.6%	4.25%

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Safetensors

Model size

9B params

Tensor type

BF16

Model tree for InflexionLab/VibeVoice-ASR-Kazakh

Base model

microsoft/VibeVoice-ASR

Adapter

(8)

this model

Dataset used to train InflexionLab/VibeVoice-ASR-Kazakh

Evaluation results

WER on ISSAI KSC2
self-reported

22%