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Intelligibility prediction with a pretrained noise-robust automatic speech recognition model.

, , and . CoRR, (2023)

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Energy-Based Models For Speech Synthesis., , and . CoRR, (2023)Acoustic Feature Extraction with Interpretable Deep Neural Network for Neurodegenerative Related Disorder Classification., , , , , , , , and . INTERSPEECH, page 4806-4810. ISCA, (2020)Unsupervised Uncertainty Measures of Automatic Speech Recognition for Non-intrusive Speech Intelligibility Prediction., , and . INTERSPEECH, page 3493-3497. ISCA, (2022)Auditory-Based Data Augmentation for end-to-end Automatic Speech Recognition., , , and . ICASSP, page 7447-7451. IEEE, (2022)Exploiting Hidden Representations from a DNN-based Speech Recogniser for Speech Intelligibility Prediction in Hearing-impaired Listeners., , and . INTERSPEECH, page 3488-3492. ISCA, (2022)Optimising Hearing Aid Fittings for Speech in Noise with a Differentiable Hearing Loss Model., , and . Interspeech, page 691-695. ISCA, (2021)DHASP: Differentiable Hearing Aid Speech Processing., , and . ICASSP, page 296-300. IEEE, (2021)The 2nd Clarity Enhancement Challenge for Hearing Aid Speech Intelligibility Enhancement: Overview and Outcomes., , , , , , , , and . ICASSP, page 1-5. IEEE, (2023)Intelligibility prediction with a pretrained noise-robust automatic speech recognition model., , and . CoRR, (2023)