A probabilistic framework for multiple speaker localization

This paper presents a novel probabilistic framework for localizing multiple speakers with a microphone array. In this framework, the generalized cross correlation function (GCC) of each microphone pair is interpreted as a probability distribution of the time difference of arrival (TDOA) and subseque...

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Vydáno v:Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 3962 - 3966
Hlavní autoři: Oualil, Youssef, Magimai-Doss, Mathew, Faubel, Friedrich, Klakow, Dietrich
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2013
Témata:
Acoustics
Arrays
Gaussian mixture
Joints
localization
Microphone arrays
Microphones
multiple speakers
Position measurement
Probabilistic logic
Speech
steered response power
ISSN:1520-6149
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Abstract This paper presents a novel probabilistic framework for localizing multiple speakers with a microphone array. In this framework, the generalized cross correlation function (GCC) of each microphone pair is interpreted as a probability distribution of the time difference of arrival (TDOA) and subsequently approximated as a Gaussian mixture. The distribution parameters are estimated with a weighted expectation maximization algorithm. Then, the joint distribution of the TDOA Gaussian mixtures is mapped to a multimodal distribution in the location space, where each mode represents a potential source location. The approach taken here performs the localization by 1) reducing the search space to some regions that are likely to contain a source and then 2) extracting the actual speaker locations with a numerical optimization algorithm. The effectiveness of the proposed approach is shown using the AV16.3 corpus.
AbstractList This paper presents a novel probabilistic framework for localizing multiple speakers with a microphone array. In this framework, the generalized cross correlation function (GCC) of each microphone pair is interpreted as a probability distribution of the time difference of arrival (TDOA) and subsequently approximated as a Gaussian mixture. The distribution parameters are estimated with a weighted expectation maximization algorithm. Then, the joint distribution of the TDOA Gaussian mixtures is mapped to a multimodal distribution in the location space, where each mode represents a potential source location. The approach taken here performs the localization by 1) reducing the search space to some regions that are likely to contain a source and then 2) extracting the actual speaker locations with a numerical optimization algorithm. The effectiveness of the proposed approach is shown using the AV16.3 corpus.
Author Klakow, Dietrich
Faubel, Friedrich
Magimai-Doss, Mathew
Oualil, Youssef
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  surname: Oualil
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  email: youssef.oualil@lsv.uni-saarland.de
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  givenname: Mathew
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  organization: Spoken Language Systems, Saarland University, Saarbrücken, Germany
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  surname: Klakow
  fullname: Klakow, Dietrich
  organization: Spoken Language Systems, Saarland University, Saarbrücken, Germany
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Snippet This paper presents a novel probabilistic framework for localizing multiple speakers with a microphone array. In this framework, the generalized cross...
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StartPage 3962
SubjectTerms Acoustics
Arrays
Gaussian mixture
Joints
localization
Microphone arrays
Microphones
multiple speakers
Position measurement
Probabilistic logic
Speech
steered response power
Title A probabilistic framework for multiple speaker localization
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