Speaker Localization with Moving Microphone Arrays
File(s)
Accepted version
Author(s)
Dorfan, Y
Evers, C
Gannot, S
Naylor, P
Type
Conference Paper
Abstract
Speaker localization algorithms often assume static
location for all sensors. This assumption simplifies the models
used, since all acoustic transfer functions are linear time invariant.
In many applications this assumption is not valid. In
this paper we address the localization challenge with moving
microphone arrays. We propose two algorithms to find the
speaker position. The first approach is a batch algorithm based
on the maximum likelihood criterion, optimized via expectationmaximization
iterations. The second approach is a particle filter
for sequential Bayesian estimation. The performance of both
approaches is evaluated and compared for simulated reverberant
audio data from a microphone array with two sensors.
location for all sensors. This assumption simplifies the models
used, since all acoustic transfer functions are linear time invariant.
In many applications this assumption is not valid. In
this paper we address the localization challenge with moving
microphone arrays. We propose two algorithms to find the
speaker position. The first approach is a batch algorithm based
on the maximum likelihood criterion, optimized via expectationmaximization
iterations. The second approach is a particle filter
for sequential Bayesian estimation. The performance of both
approaches is evaluated and compared for simulated reverberant
audio data from a microphone array with two sensors.
Date Issued
2016-12-01
Date Acceptance
2016-06-16
Citation
Proc. European Signal Processing Conference (EUSIPCO), 2016
ISSN
2076-1465
Publisher
IEEE
Journal / Book Title
Proc. European Signal Processing Conference (EUSIPCO)
Copyright Statement
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Commission of the European Communities
Grant Number
609465
Source
European Signal Processing Conference (EUSIPCO)
Subjects
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
TRACKING
Publication Status
Published
Start Date
2016-08-29
Finish Date
2016-09-02
Coverage Spatial
Budapest, Hungary