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Titlebook: Man-Machine Speech Communication; 17th National Confer Ling Zhenhua,Gao Jianqing,Jia Jia Conference proceedings 2023 The Editor(s) (if appl

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發(fā)表于 2025-3-25 03:26:55 | 只看該作者
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發(fā)表于 2025-3-26 04:20:25 | 只看該作者
,Semantic Enhancement Framework for?Robust Speech Recognition,t of the ASR system will provide input to the subsequent system, the semantic intelligibility problem of the recognition results draws wide attention, yet remains unsolved. We propose a semantic enhancement framework to extract global semantic information from the audio to guide the recognition resu
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發(fā)表于 2025-3-26 09:41:22 | 只看該作者
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發(fā)表于 2025-3-26 12:51:00 | 只看該作者
Predictive AutoEncoders Are Context-Aware Unsupervised Anomalous Sound Detectors,he conventional unsupervised ASD approaches mainly employ the straightforward deep neural network?(DNN) to detect abnormal sounds. However, this model fails to consider the utilization of the relationship between frames, resulting in limited performance and constrained input length. Recently, contex
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發(fā)表于 2025-3-26 18:25:30 | 只看該作者
,A Pipelined Framework with?Serialized Output Training for?Overlapping Speech Recognition,paper, we focus on solving the problem of overlapping speech and present a pipelined architecture with serialized output training(SOT). The baseline and the proposed methods are evaluated on the artificially mixed speech datasets generated from the AliMeeting corpus. Experimental results demonstrate
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