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Rus Heywood

2 accepted papers

2024

Large Language Models As A Proxy For Human Evaluation In Assessing The Comprehensibility Of Disordered Speech Transcription

ICASSP 2024accepted

Automatic Speech Recognition (ASR) systems, despite significant advances in recent years, still have much room for improvement particularly in the recognition of disordered speech. Even so, erroneous transcripts from ASR models can help people with disordered speech be better understood, especially…

Cited by 0SourceScholar
2023

Speech Intelligibility Classifiers from 550k Disordered Speech Samples

ICASSP 2023accepted

We developed dysarthric speech intelligibility classifiers on 551,176 disordered speech samples contributed by a diverse set of 468 speakers, with a range of self-reported speaking disorders and rated for their overall intelligibility on a five-point scale. We trained three models following differen…

Cited by 0SourceScholar