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publications
Unveiling the Best Practices for Applying Speech Foundation Models to Speech Intelligibility Prediction for Hearing-Impaired People
Published in WASPAA, 2025
Speech foundation models (SFMs) have shown strong performance across various downstream tasks, including speech intelligibility prediction. In this paper, we provide a comprehensive guide highlighting the key considerations necessary to maximize prediction performance.
Recommended citation: Zhou, H., Cao, B., Mo, C., Li, L., & Wang, S. X. (2025). Unveiling the Best Practices for Applying Speech Foundation Models to Speech Intelligibility Prediction for Hearing-Impaired People. WASPAA 2025.
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No Audiogram: Leveraging Existing Scores for Personalized Speech Intelligibility Prediction
Published in Interspeech, 2025
In this paper, instead of using audiograms, we propose a new paradigm for personalized speech intelligibility prediction, which utilizes one’s existing intelligibility scores to predict the intelligibility score on new audio clips.
Recommended citation: Zhou, H., Mo, C., Cao, B., Li, L., & Wang, S. X. (2025). No Audiogram: Leveraging Existing Scores for Personalized Speech Intelligibility Prediction. Interspeech 2025.
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Intrusive Intelligibility Prediction with ASR Encoders
Published in Interspeech, 2025
Speech foundation models have demonstrated strong performance in speech intelligibility prediction. In this paper, we present a set of practical techniques that enabled us to achieve first place in the Third Clarity Prediction Challenge.
Recommended citation: Yu, H., Zhou, H., Cao, B., Mo, C., Li, L., & Wang, S. X. (2025, August). Intrusive Intelligibility Prediction with ASR Encoders. In Clarity-2025: The 6th Clarity Workshop on Improving Speech-in-Noise for Hearing Devices (Satellite of Interspeech 2025), Delft, The Netherlands.
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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