whisper-yoad-small-he-acft – AI Model by amitkot | AlphaNeural AI

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amitkot/
whisper-yoad-small-he-acft

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automatic-speech-recognition

speech-recognition

yoad/whisper-small

endpoints_compatible

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whisper-yoad-small-he-acft

ACFT (Audio Context Fine-Tuning) applied to yoad/whisper-small for Hebrew speech recognition.

ACFT aligns partial-context encoder representations with full-context ones, improving short-utterance inference (e.g., keyboard dictation).

Evaluation

WER on ivrit-ai/whisper-training test split (2000 samples, no normalization):

Model	WER
yoad/whisper-small (base)	0.2704
yoad/whisper-small + ACFT (this model)	0.2540

Training

Method: ACFT (encoder MSE alignment)
Dataset: google/fleurs he_il
Epochs: 8
Device: Apple MPS (M4 Pro)

Usage

python

from transformers import WhisperForConditionalGeneration, WhisperProcessor

model = WhisperForConditionalGeneration.from_pretrained("amitkot/whisper-yoad-small-he-acft")
processor = WhisperProcessor.from_pretrained("amitkot/whisper-yoad-small-he-acft")