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Demand-Aware Opportunistic Spectrum Access: A Game-Theoretic Learning Approach Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Multi-speaker Recognition in Cocktail Party Problem

Authors : Yiqian Wang, Wensheng Sun

Published in: Communications, Signal Processing, and Systems

Publisher: Springer Singapore

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Abstract

This paper proposes an original statistical decision theory to accomplish a multi-speaker recognition task in cocktail party problem. This theory relies on an assumption that the varied frequencies of speakers obey Gaussian distribution and the relationship of their voiceprints can be represented by Euclidean distance vectors. This paper uses Mel-Frequency Cepstral Coefficients to extract the feature of a voice in judging whether a speaker is included in a multi-speaker environment and distinguish who the speaker should be. Finally, a thirteen-dimension constellation drawing is established by mapping from Manhattan distances of speakers in order to take a thorough consideration about gross influential factors.

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Metadata
Title
Multi-speaker Recognition in Cocktail Party Problem
Authors
Yiqian Wang
Wensheng Sun
Copyright Year
2019
Publisher
Springer Singapore
Book
Communications, Signal Processing, and Systems

Print ISBN: 978-981-10-6570-5

Electronic ISBN: 978-981-10-6571-2

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-10-6571-2_258