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Open Access

Single-Channel Talker Localization Based on Discrimination of Acoustic Transfer Functions

  • Tetsuya Takiguchi1Email author,
  • Yuji Sumida1,
  • Ryoichi Takashima1 and
  • Yasuo Ariki1
EURASIP Journal on Advances in Signal Processing20092009:918404

Received: 5 June 2008

Accepted: 5 February 2009

Published: 17 March 2009


This paper presents a sound source (talker) localization method using only a single microphone, where a Gaussian Mixture Model (GMM) of clean speech is introduced to estimate the acoustic transfer function from a user's position. The new method is able to carry out this estimation without measuring impulse responses. The frame sequence of the acoustic transfer function is estimated by maximizing the likelihood of training data uttered from a given position, where the cepstral parameters are used to effectively represent useful clean speech. Using the estimated frame sequence data, the GMM of the acoustic transfer function is created to deal with the influence of a room impulse response. Then, for each test dataset, we find a maximum-likelihood (ML) GMM from among the estimated GMMs corresponding to each position. The effectiveness of this method has been confirmed by talker localization experiments performed in a room environment.


Mixture ModelImpulse ResponseQuantum InformationGaussian Mixture ModelSound Source

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Authors’ Affiliations

Organization of Advanced Science and Technology, Kobe University, Kobe, Japan


© Tetsuya Takiguchi et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.