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Speaker-Utterance Dual Attention for Speaker and Utterance Verification

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Document pages: 5 pages

Abstract: In this paper, we study a novel technique that exploits the interactionbetween speaker traits and linguistic content to improve both speakerverification and utterance verification performance. We implement an idea ofspeaker-utterance dual attention (SUDA) in a unified neural network. The dualattention refers to an attention mechanism for the two tasks of speaker andutterance verification. The proposed SUDA features an attention mask mechanismto learn the interaction between the speaker and utterance information streams.This helps to focus only on the required information for respective task bymasking the irrelevant counterparts. The studies conducted on RSR2015 corpusconfirm that the proposed SUDA outperforms the framework without attention maskas well as several competitive systems for both speaker and utteranceverification.

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