Vocabulary Constrained Decoding

via “vocabulary-constrained-decoding”

automatic-speech-recognition model by undefined. 49,28,734 downloads.

Unique: Implements vocabulary constraints via masked beam search decoding, restricting token selection at each step to predefined vocabulary. Operates within the standard Whisper decoding pipeline without requiring model retraining or fine-tuning.

vs others: Simpler to implement than domain-specific fine-tuning because it requires only vocabulary lists, not labeled training data; however, less accurate than fine-tuned models because the base model is not adapted to the domain, and constrained decoding forces suboptimal token choices.

via “vocabulary-constrained-decoding-with-language-model-integration”

automatic-speech-recognition model by undefined. 10,07,776 downloads.

Unique: Decouples acoustic modeling (wav2vec2) from language modeling, enabling flexible integration of domain-specific Japanese LMs without retraining the acoustic model. This modular approach allows swapping LMs for different domains while keeping the same pretrained acoustic features.

vs others: Improves accuracy on specialized vocabularies without fine-tuning the acoustic model, and is more flexible than end-to-end models that bake in language modeling, allowing rapid adaptation to new domains.