Guo, Y. orcid.org/0000-0002-0307-1459, Wang, X., Wu, C. et al. (3 more authors) (2016) A robust dual-microphone speech source localization algorithm for reverberant environments. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Interspeech, 08-12 Sep 2016, San Francisco, USA. ISCA
Abstract
Speech source localization (SSL) using a microphone array aims to estimate the direction-of-arrival (DOA) of the speech source. However, its performance often degrades rapidly in reverberant environments. In this paper, a novel dual-microphone SSL algorithm is proposed to address this problem. First, the time-frequency regions dominated by direct sound are extracted by tracking the envelopes of speech, reverberation and background noise. The time-difference-of-arrival (TDOA) is then estimated by considering only these reliable regions. Second, a bin-wise de-aliasing strategy is introduced to make better use of the DOA information carried at high frequencies, where the spatial resolution is higher and there is typically less corruption by diffuse noise. Our experiments show that when compared with other widely-used algorithms, the proposed algorithm produces more reliable performance in realistic reverberant environments.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2016 ISCA |
Keywords: | Microphone array; Speech source localization; direction of arrival; reverberation |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - FP6/FP7 TWO!EARS - 618075 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 20 Jul 2016 09:20 |
Last Modified: | 19 Dec 2022 13:34 |
Published Version: | https://doi.org/10.21437/Interspeech.2016-1063 |
Status: | Published |
Publisher: | ISCA |
Refereed: | Yes |
Identification Number: | 10.21437/Interspeech.2016-1063 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:102624 |