Improved Speech Activity Detection Using Cross-Channel Features for Recognition of Multiparty Meetings
Title | Improved Speech Activity Detection Using Cross-Channel Features for Recognition of Multiparty Meetings |
Publication Type | Conference Paper |
Year of Publication | 2006 |
Authors | Boakye, K., & Stolcke A. |
Published in | Proceedings of the 9th International Conference on Spoken Language Processing (ICSLP-Interspeech 2006) |
Page(s) | 1962-1965 |
Other Numbers | 2058 |
Abstract | We describe the development of a speech activity detection system using an HMM-based segmenter for automatic speech recognition on individual headset microphones in multispeaker meetings. We look at cross-channel features (energy and correlation based) to incorporate into the segmenter for the purpose of addressing errors related to cross-channel phenomena such as crosstalk. Results demonstrate that these features provide a marked improvement (18% relative) over a baseline system using single-channel features as well as an improvement (8% relative) over our previous solution of separate speech activity detection and cross-channel analysis. In addition, the simple cross-channel energy features are shown to be more robust - and consequently better performing - than the more common correlation-based features. |
URL | http://www.icsi.berkeley.edu/pubs/speech/boakye_stolcke.pdf |
Bibliographic Notes | Proceedings of the 9th International Conference on Spoken Language Processing (ICSLP-Interspeech 2006), Pittsburgh, Pennsylvania, pp. 1962-1965 |
Abbreviated Authors | K. Boakye and A. Stolcke |
ICSI Research Group | Speech |
ICSI Publication Type | Article in conference proceedings |