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fuann/
hmamba-full-distilled

Name: hmamba-full-distilled
Availability: InStock

pytorch

safetensors

hmamba

pronunciation-assessment

speechocean762

mamba

apache-2.0

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Distilled HMamba for SpeechOcean762

This repository contains the HMamba inference core used for phone-, word-, and utterance-level English pronunciation assessment. It is intended to be used with the run_hmamba_infer.sh pipeline from the HMamba repository.

This is not a waveform-to-score model by itself. The script supplies the required Kaldi GOP, phone alignment, Wav2Vec2, HuBERT, WavLM, and raw acoustic features.

bash

bash run_hmamba_infer.sh \
  --model-source USERNAME/hmamba-full-distilled \
  --wav example.wav \
  --utt-id example_0001 \
  --text "REFERENCE TRANSCRIPT"

Files

model.safetensors: distilled HMamba weights
config.json: architecture and preprocessing contract
vocab.json: phone-to-ID mapping

Important limitations

Input audio must have a reference English transcript.
The model supports at most 52 aligned phone tokens.
The original implementation requires CUDA-compatible mamba-ssm and Triton.
Model outputs should not be interpreted as clinical or diagnostic results.

Feature contract

GOP: 84 dimensions, normalized with mean 3.203 and standard deviation 4.045
SSL order: Wav2Vec2 XLSR-53, HuBERT LL60K, WavLM Large
SSL dimension: 1024 per model
Raw input file: 17 dimensions; HMamba consumes duration plus the first seven energy statistics (indices 0 through 7)
Phone scores use the 0-2 scale
Word and utterance scores are multiplied by 5 for the 0-10 presentation scale

fuann/hmamba-full-distilled

Distilled HMamba for SpeechOcean762

Files

Important limitations

Feature contract

fuann/
hmamba-full-distilled