Dual-channel speech separation using interaural time difference with Generalized Gaussian Mixture Model
Authors
Zhaogui Ding, Liming Zhang, Longbiao Wang, Weifeng Li
Corresponding Author
Zhaogui Ding
Available Online October 2015.
- DOI
- 10.2991/icitmi-15.2015.194How to use a DOI?
- Keywords
- interaural time difference (ITD) statistics, Generalized Gaussian Mixture Model, correlation coefficient, time-frequency mask
- Abstract
In this letter we present a novel speech separation scheme using two microphones. The proposed method utilizes the estimation of interaural time difference (ITD) statistics for the separation of mixed speech sources. The novelties of this paper consist in the use of Generalized Gaussian Mixture Model (GGMM) for speech separation frame by frame and cross-correlation coefficient for distributed parameter selection. The proposed model can be extended to audio enhancement. Our objective quality evaluation experiments demonstrate the effectiveness of the proposed methods and show significant quality improvements over the conventional dual ITD based methods.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhaogui Ding AU - Liming Zhang AU - Longbiao Wang AU - Weifeng Li PY - 2015/10 DA - 2015/10 TI - Dual-channel speech separation using interaural time difference with Generalized Gaussian Mixture Model BT - Proceedings of the 4th International Conference on Information Technology and Management Innovation PB - Atlantis Press SP - 1157 EP - 1163 SN - 2352-538X UR - https://doi.org/10.2991/icitmi-15.2015.194 DO - 10.2991/icitmi-15.2015.194 ID - Ding2015/10 ER -