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The 1st Clarity Prediction Challenge: A machine learning challenge for hearing aid intelligibility prediction.

, , , , , , , , , , , and . INTERSPEECH, page 3508-3512. ISCA, (2022)

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Deep Learning of Articulatory-Based Representations and Applications for Improving Dysarthric Speech Recognition., , and . ITG Symposium on Speech Communication, page 1-5. VDE / IEEE, (2018)Missing-Data Techniques: Recognition with Incomplete Spectrograms.. Techniques for Noise Robustness in Automatic Speech Recognition, Wiley, (2012)Malware Detection by Eating a Whole EXE., , , , , and . AAAI Workshops, volume WS-18 of AAAI Technical Report, page 268-276. AAAI Press, (2018)Soft decisions in missing data techniques for robust automatic speech recognition., , , and . INTERSPEECH, page 373-376. ISCA, (2000)Decoding speech in the presence of other sound sources., , and . INTERSPEECH, page 270-273. ISCA, (2000)Acoustic confidence measures for segmenting broadcast news., , and . ICSLP, ISCA, (1998)The use of Voice Source Features for Sung Speech Recognition., and . ICASSP, page 6513-6517. IEEE, (2021)Multi-Modal Acoustic-Articulatory Feature Fusion For Dysarthric Speech Recognition., , , , and . ICASSP, page 7372-7376. IEEE, (2022)An audio-visual corpus for speech perception and automatic speech recognition, , , and . The Journal of the Acoustical Society of America, 120 (5): 2421-2424 (November 2006)Phonetic Analysis of Dysarthric Speech Tempo and Applications to Robust Personalised Dysarthric Speech Recognition., , and . ICASSP, page 5836-5840. IEEE, (2019)