Rescoring of N-Best Hypotheses Using Top-Down Selective Attention for Automatic Speech Recognition.

IEEE Signal Processing Letters(2018)

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摘要
In this letter, we propose an N-best rescoring system that integrates attentional information for locally confusing words extracted from alternative hypotheses to a conventional speech recognition system. The attentional information is derived by adapting a test input feature for the word of interest, which is motivated by the top-down selective attention mechanism of the brain. To rescore the com...
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关键词
Speech recognition,Acoustics,Indexes,Speech,Training,Feature extraction
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