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Multi-Channel Speech Enhancement and Amplitude Modulation Analysis for Noise Robust Automatic Speech Recognition.

, , , , and . Comput. Speech Lang., (2017)

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Digital hearing aid techniques employing a loudness model for recruitment compensation., and . ICSLP, page 2111-2114. ISCA, (1994)Multi-loudspeaker equalization for acoustic transparency in a custom hearing device., , , and . ITG Symposium on Speech Communication, page 1-5. VDE / IEEE, (2018)Classifier Architectures for Acoustic Scenes and Events: Implications for DNNs, TDNNs, and Perceptual Features from DCASE 2016., , , , and . IEEE ACM Trans. Audio Speech Lang. Process., 25 (6): 1304-1314 (2017)Does sentence complexity interfere with intelligibility in noise? evaluation of the oldenburg linguistically and audiologically controlled sentence test (OLACS)., , , , , , and . INTERSPEECH, page 2482-2485. ISCA, (2010)Prediction of Binaural Intelligibility Level Differences in Reverberation., , and . INTERSPEECH, page 37-40. ISCA, (2011)Acoustic Scene Classification using Time-Delay Neural Networks and Amplitude Modulation Filter Bank Features., , , , and . DCASE, page 70-74. (2016)A quantitative model of the effective signal processing in the auditory system. I. Model structure, , and . Acoustical Society of America, (1996)A quantitative model of the effective signal processing in the auditory system. II. Simulations and measurements, , and . Acoustical Society of America, (1996)Modeling auditory processing of amplitude modulation. I. Detection and masking with narrow-band carriers, , and . Acoustical Society of America, (1997)Modulation-based detection of speech in real background noise: Generalization to novel background classes., , and . ICASSP, page 41-44. IEEE, (2010)