A Phoneme-Scale Assessment of Multichannel Speech Enhancement Algorithms. [PDF]
Trends HearMonir NE, Magron P, Serizel R.
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A talker-independent deep learning algorithm to increase intelligibility for hearing-impaired listeners in reverberant competing talker conditions. [PDF]
J Acoust Soc Am, 2020 Healy EW +3 more
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Blind Convolutive Speech Separation and Dereverberation.
, 2012 Extraction of a target speech signal from the convolutive mixture of multiple sources observed in a cocktail party environment is a challenging task, especially when the room acoustic effects and background noise are present in the environment. Such acoustic distortions may further degrade the separation performance of many existing source separation ...
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Concentration, motivation, activity, and subjective fatigue in patients with single-sided deafness. [PDF]
J Laryngol OtolGürses E, Kılıç S, Çıldır B.
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Two-stage Deep Learning for Noisy-reverberant Speech Enhancement. [PDF]
IEEE/ACM Trans Audio Speech Lang Process, 2019 Zhao Y, Wang ZQ, Wang D.
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Compression of room impulse responses for compact storage and fast low-latency convolution. [PDF]
EURASIP J Audio Speech Music ProcessJälmby M +2 more
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Deep Learning for Talker-dependent Reverberant Speaker Separation: An Empirical Study. [PDF]
IEEE/ACM Trans Audio Speech Lang Process, 2019 Delfarah M, Wang D.
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Adaptation to Reverberation for Speech Perception: A Systematic Review. [PDF]
Trends HearTsironis A +4 more
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Enhancing speaker identification through reverberation modeling and cancelable techniques using ANNs. [PDF]
PLoS OneHassan ES +6 more
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Supervised Speech Separation Based on Deep Learning: An Overview. [PDF]
IEEE/ACM Trans Audio Speech Lang Process, 2018 Wang D, Chen J.
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