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Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups

, , , , , , , , , , and . IEEE Signal Processing Magazine, 29 (6): 82--97 (2012)

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Speech recognition for medical conversations., , , , , , , , , and 4 other author(s). CoRR, (2017)Joint n-best rescoring for repeated utterances in spoken dialog systems., , , and . SLT, page 133-136. IEEE, (2008)RNN-T Models Fail to Generalize to Out-of-Domain Audio: Causes and Solutions., , , , , , , , , and 1 other author(s). CoRR, (2020)Multi-scale Personalization for Voice Search Applications., , and . HLT-NAACL (Short Papers), page 101-104. The Association for Computational Linguistics, (2009)On the Choice of Modeling Unit for Sequence-to-Sequence Speech Recognition., , , , , and . INTERSPEECH, page 3800-3804. ISCA, (2019)Structured models for joint decoding of repeated utterances., , , and . INTERSPEECH, page 1157-1160. ISCA, (2008)Maximum-likelihood training of a bipartite acoustic model for speech recognition., , , and . INTERSPEECH, page 683-686. ISCA, (2001)SCARF: a segmental conditional random field toolkit for speech recognition., and . INTERSPEECH, page 2858-2861. ISCA, (2010)Continuous speech recognition with a TF-IDF acoustic model., , , and . INTERSPEECH, page 2854-2857. ISCA, (2010)Large corpus experiments for broadcast news recognition., , and . INTERSPEECH, page 1837-1840. ISCA, (2003)