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Front-end technologies for robust ASR in reverberant environments - spectral enhancement-based dereverberation and auditory modulation filterbank features.

, , , , , , , and . EURASIP J. Adv. Signal Process., (2015)

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Temporal variability of spectro-temporal receptive fields in the anesthetized auditory cortex., , , and . Frontiers Comput. Neurosci., (2014)Multi-Channel Speech Enhancement and Amplitude Modulation Analysis for Noise Robust Automatic Speech Recognition., , , , and . Comput. Speech Lang., (2017)Multi-channel signal enhancement with speech and noise covariance estimates computed by a probabilistic localization model., and . ICASSP, page 156-160. IEEE, (2017)Audio Classification and Localization for Incongruent Event Detection., , and . Detection and Identification of Rare Audiovisual Cues, volume 384 of Studies in Computational Intelligence, Springer, (2012)Towards end-to-end speech enhancement with a variational U-Net architecture., and . CoRR, (2020)The DIRAC AWEAR audio-visual platform for detection of unexpected and incongruent events., , , , , , , , , and 4 other author(s). ICMI, page 289-292. ACM, (2008)Amplitude modulation spectrogram based features for robust speech recognition in noisy and reverberant environments., , and . ICASSP, page 5492-5495. IEEE, (2011)Complex Independent Component Analysis of Frequency-Domain Electroencephalographic Data, , and . CoRR, (2003)An Auditory Inspired Amplitude Modulation Filter Bank for Robust Feature Extraction in Automatic Speech Recognition., , and . IEEE ACM Trans. Audio Speech Lang. Process., 23 (11): 1926-1937 (2015)Predictability of STRFs in auditory cortex neurons depends on stimulus class., , , and . INTERSPEECH, page 670. ISCA, (2008)