ClaraVox models

The two models behind ClaraVox, an app that turns atypical speech into clear spoken English.

Folder What it is Base model
whisper-sap-v3/ Speech to text, fine-tuned on 384 h of atypical speech from 648 speakers (used by the app) openai/whisper-small
whisper-sap-v2/ Second speech run, 82 h openai/whisper-small
whisper-sap-v1/ First speech run, 57 h subset openai/whisper-small
gec-v2/ Grammar correction that keeps the speaker's meaning (prefix Fix grammar: ) google/flan-t5-base

Speech model results

Word error rate on held-out speakers from the Speech Accessibility Project (never seen in training, 300 clips per group):

Model ALS Cerebral palsy Down syndrome Parkinson's Stroke All
whisper-small, no training 76.3% 48.4% 46.5% 22.1% 42.2% 43.3%
whisper-sap-v1 16.4% 22.8% 14.3% 16.6% 32.5% 19.7%
whisper-sap-v2 16.6% 23.2% 13.8% 15.2% 31.1% 19.0%
whisper-sap-v3 14.1% 19.6% 11.6% 11.9% 36.8% 17.4%

The test set has only 2–6 speakers per group, so the per-group numbers are rough.

On a larger test set of 62 held-out speakers (1,500 clips), v2 scores 14.0% and v3 12.5% (ALS 7.0%, cerebral palsy 17.4%, Down syndrome 19.5%, Parkinson's 7.2%, stroke 17.6%).

Use

from transformers import WhisperProcessor, WhisperForConditionalGeneration, AutoTokenizer, AutoModelForSeq2SeqLM
repo = "PINEAPPLEANANAS/ClaraVox-models"
proc = WhisperProcessor.from_pretrained(repo, subfolder="whisper-sap-v3")
asr = WhisperForConditionalGeneration.from_pretrained(repo, subfolder="whisper-sap-v3")
tok = AutoTokenizer.from_pretrained(repo, subfolder="gec-v2")
gec = AutoModelForSeq2SeqLM.from_pretrained(repo, subfolder="gec-v2")

Training data and credits

  • Speech Accessibility Project, University of Illinois Urbana-Champaign. Used under a Data Transfer and Use Agreement. These models are Results under that agreement and contain no SAP audio or transcripts.
  • TORGO dysarthric speech database, University of Toronto.
  • TalkBank corpora and JFLEG (grammar model).

Code and full training details: https://github.com/TanayMangal/Clara-Vox

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