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DF-Conformer: Integrated Architecture of Conv-Tasnet and Conformer Using Linear Complexity Self-Attention for Speech Enhancement.

, , , , , , and . WASPAA, page 161-165. IEEE, (2021)

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State-of-the-art Speech Recognition With Sequence-to-Sequence Models., , , , , , , , , and 4 other author(s). CoRR, (2017)Multi-Dialect Speech Recognition With A Single Sequence-To-Sequence Model., , , , , , , , and . CoRR, (2017)Multichannel Signal Processing With Deep Neural Networks for Automatic Speech Recognition., , , , , , , , , and 2 other author(s). IEEE ACM Trans. Audio Speech Lang. Process., 25 (5): 965-979 (2017)Speech recognition based on acoustically derived segment units., , , and . ICSLP, page 1077-1080. ISCA, (1996)Combining maximum likelihood and maximum a posteriori estimation for detailed acoustic modeling of context dependency.. INTERSPEECH, page 2593-2596. ISCA, (2002)Efficient Implementation of the Room Simulator for Training Deep Neural Network Acoustic Models., , , and . INTERSPEECH, page 3028-3032. ISCA, (2018)SCANMail: a voicemail interface that makes speech browsable, readable and searchable., , , , , , , , and . CHI, page 275-282. ACM, (2002)From Audio to Semantics: Approaches to End-to-End Spoken Language Understanding., , , , , , , , and . SLT, page 720-726. IEEE, (2018)Joint Phoneme-Grapheme Model for End-To-End Speech Recognition., and . ICASSP, page 6119-6123. IEEE, (2020)Confidence scores for acoustic model adaptation., and . ICASSP, page 4289-4292. IEEE, (2008)