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Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting.

M. Sun, A. Raju, G. Tucker, S. Panchapagesan, G. Fu, A. Mandal, S. Matsoukas, N. Strom, and S. Vitaladevuni. CoRR, (2017)

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Data Augmentation for Robust Keyword Spotting under Playback Interference.A. Raju, S. Panchapagesan, X. Liu, A. Mandal, and N. Strom. CoRR, (2018)Model Compression Applied to Small-Footprint Keyword Spotting.G. Tucker, M. Wu, M. Sun, S. Panchapagesan, G. Fu, and S. Vitaladevuni. INTERSPEECH, page 1878-1882. ISCA, (2016)Multi-Parameter Frequency Warping for Vtln by Gradient Search.S. Panchapagesan, and A. Alwan. ICASSP (1), page 1181-1184. IEEE, (2006)Monophone-Based Background Modeling for Two-Stage On-Device Wake Word Detection.M. Wu, S. Panchapagesan, M. Sun, J. Gu, R. Thomas, S. Vitaladevuni, B. Hoffmeister, and A. Mandal. ICASSP, page 5494-5498. IEEE, (2018)Multi-Task Learning and Weighted Cross-Entropy for DNN-Based Keyword Spotting.S. Panchapagesan, M. Sun, A. Khare, S. Matsoukas, A. Mandal, B. Hoffmeister, and S. Vitaladevuni. INTERSPEECH, page 760-764. ISCA, (2016)Frequency warping for VTLN and speaker adaptation by linear transformation of standard MFCC.S. Panchapagesan, and A. Alwan. Computer Speech & Language, 23 (1): 42-64 (2009)Frequency warping by linear transformation of standard MFCC.S. Panchapagesan. INTERSPEECH, ISCA, (2006)Vocal tract inversion by cepstral analysis-by-synthesis using chain matrices.S. Panchapagesan, and A. Alwan. INTERSPEECH, page 2857-2860. ISCA, (2008)Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting.M. Sun, A. Raju, G. Tucker, S. Panchapagesan, G. Fu, A. Mandal, S. Matsoukas, N. Strom, and S. Vitaladevuni. CoRR, (2017)Compressed Time Delay Neural Network for Small-Footprint Keyword Spotting.M. Sun, D. Snyder, Y. Gao, V. Nagaraja, M. Rodehorst, S. Panchapagesan, N. Strom, S. Matsoukas, and S. Vitaladevuni. INTERSPEECH, page 3607-3611. ISCA, (2017)

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Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting.

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Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting.