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Cross attentive pooling for speaker verification

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Document pages: 7 pages

Abstract: The goal of this paper is text-independent speaker verification whereutterances come from in the wild videos and may contain irrelevant signal.While speaker verification is naturally a pair-wise problem, existing methodsto produce the speaker embeddings are instance-wise. In this paper, we proposeCross Attentive Pooling (CAP) that utilizes the context information across thereference-query pair to generate utterance-level embeddings that contain themost discriminative information for the pair-wise matching problem. Experimentsare performed on the VoxCeleb dataset in which our method outperformscomparable pooling strategies.

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