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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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Amplitude modulation spectrogram based features for robust speech recognition in noisy and reverberant environments., , and . ICASSP, page 5492-5495. IEEE, (2011)Probabilistic Spatial Filter Estimation for Signal Enhancement in Multi-Channel Automatic Speech Recognition., , and . INTERSPEECH, page 2562-2566. ISCA, (2016)Streaming End-to-End Speech Recognition with Joint CTC-Attention Based Models., , and . ASRU, page 936-943. IEEE, (2019)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)Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition., , and . INTERSPEECH, page 76-80. ISCA, (2019)Triggered Attention for End-to-end Speech Recognition., , and . ICASSP, page 5666-5670. IEEE, (2019)Integration of Optimized Modulation Filter Sets Into Deep Neural Networks for Automatic Speech Recognition., , and . IEEE ACM Trans. Audio Speech Lang. Process., 24 (12): 2439-2452 (2016)Unsupervised Speaker Adaptation Using Attention-Based Speaker Memory for End-to-End ASR., , , and . ICASSP, page 7384-7388. IEEE, (2020)Amplitude Modulation Filters as Feature Sets for Robust ASR: Constant Absolute or Relative Bandwidth?, , and . INTERSPEECH, page 1231-1234. ISCA, (2012)Objective Assessment of a Speech Enhancement Scheme with an Automatic Speech Recognition-Based System., , , , , and . ITG Symposium on Speech Communication, page 1-5. VDE / IEEE, (2018)