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On The Model Size Selection For Speaker Identification (2204.01294v1)
Published 4 Apr 2022 in cs.SD and eess.AS
Abstract: In this paper we evaluate the relevance of the model size for speaker identification. We show that it is possible to improve the identification rates if a different model size is used for each speaker. We also present some criteria for selecting the model size, and a new algorithm that outperforms the classical system with a fixed model size.
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