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Timestamp-aligning and keyword-biasing end-to-end ASR front-end for a KWS system

Abstract Many end-to-end approaches have been proposed to detect predefined keywords. For scenarios of multi-keywords, there are still two bottlenecks that need to be resolved: (1) the distribution of important data that contains keyword(s) is sparse, and (2) the timestamps of the detected keywords...

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Principais autores: Gui-Xin Shi, Wei-Qiang Zhang, Guan-Bo Wang, Jing Zhao, Shu-Zhou Chai, Ze-Yu Zhao
Format: Artigo
Sprog:Inglês
Udgivet: SpringerOpen 2021-07-01
Serier:EURASIP Journal on Audio, Speech, and Music Processing
Fag:
OpenSAT20
End-to-end ASR
End-to-end KWS
Force alignment
Biased loss
Online adgang:https://doi.org/10.1186/s13636-021-00212-9
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