CONF lathoud03b/IDIAP Segmenting Multiple Concurrent Speakers Using Microphone Arrays Lathoud, Guillaume McCowan, Iain A. Moore, Darren EXTERNAL https://publications.idiap.ch/attachments/papers/2003/lathoud_eurospeech2003.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/lathoud-rr-03-21 Related documents Proceedings of Eurospeech 2003 2003 Geneva, Switzerland September 2003 IDIAP-RR 03-21 Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap,',','), as is typically the case in multi-party conversations. In such cases, the location of the speaker, as measured using a microphone array, may provide greater discrimination than traditional spectral features. This was verified in previous work which obtained a global segmentation in terms of single speaker classes, as well as possible overlap combinations. However, such a global strategy suffers from an explosion of the number of overlap classes, as each possible combination of concurrent speakers must be modeled explicitly. In this paper, we propose two alternative schemes that produce an individual segmentation decision for each speaker, implicitly handling all overlapping speaker combinations. The proposed approaches also allow straightforward online implementations. Experiments are presented comparing the segmentation with that obtained using the previous system. REPORT lathoud-rr-03-21/IDIAP Segmenting Multiple Concurrent Speakers Using Microphone Arrays Lathoud, Guillaume McCowan, Iain A. Moore, Darren EXTERNAL https://publications.idiap.ch/attachments/reports/2003/rr-03-21.pdf PUBLIC Idiap-RR-21-2003 2003 IDIAP Martigny, Switzerland Published in ``Proceedings of Eurospeech 2003'' Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap,',','), as is typically the case in multi-party conversations. In such cases, the location of the speaker, as measured using a microphone array, may provide greater discrimination than traditional spectral features. This was verified in previous work which obtained a global segmentation in terms of single speaker classes, as well as possible overlap combinations. However, such a global strategy suffers from an explosion of the number of overlap classes, as each possible combination of concurrent speakers must be modeled explicitly. In this paper, we propose two alternative schemes that produce an individual segmentation decision for each speaker, implicitly handling all overlapping speaker combinations. The proposed approaches also allow straightforward online implementations. Experiments are presented comparing the segmentation with that obtained using the previous system.