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Disordered Speech Data Collection: Lessons Learned at 1 Million Utterances from Project Euphonia.

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"The less I type, the better": How AI Language Models can Enhance or Impede Communication for AAC Users., , , , , and . CHI, page 830:1-830:14. ACM, (2023)Automatic Speech Recognition of Disordered Speech: Personalized Models Outperforming Human Listeners on Short Phrases., , , , , , , , , and 2 other author(s). Interspeech, page 4778-4782. ISCA, (2021)Disordered Speech Data Collection: Lessons Learned at 1 Million Utterances from Project Euphonia., , , , , , , , , and 2 other author(s). Interspeech, page 4833-4837. ISCA, (2021)Large Language Models As A Proxy For Human Evaluation In Assessing The Comprehensibility Of Disordered Speech Transcription., , , , , , and . ICASSP, page 10846-10850. IEEE, (2024)An Analysis of Degenerating Speech Due to Progressive Dysarthria on ASR Performance., , , , , and . ICASSP, page 1-5. IEEE, (2023)Learnings from curating a trustworthy, well-annotated, and useful dataset of disordered English speech., , , , , , , , and . CoRR, (2024)Assessing ASR Model Quality on Disordered Speech using BERTScore., , , , , and . CoRR, (2022)Speech Intelligibility Classifiers from 550k Disordered Speech Samples., , , , , , , , , and . ICASSP, page 1-5. IEEE, (2023)A Voice-Activated Switch for Persons with Motor and Speech Impairments: Isolated-Vowel Spotting Using Neural Networks., , , , , , and . Interspeech, page 4823-4827. ISCA, (2021)