Abstract
In this paper, we consider speaker identification
for the co-channel scenario in which speech mixture from
speakers is recorded by one microphone only. The goal is to
identify both of the speakers from their mixed signal. High
recognition accuracies have already been reported when an
accurately estimated signal-to-signal ratio (SSR) is available. In
this paper, we approach the problem without estimating SSR.
We show that a simple method based on fusion of adapted
Gaussian mixture models and Kullback-Leibler divergence
calculated between models, achieves an accuracy of 97% and
93% when the two target speakers enlisted as three and two
most probable speakers, respectively.
for the co-channel scenario in which speech mixture from
speakers is recorded by one microphone only. The goal is to
identify both of the speakers from their mixed signal. High
recognition accuracies have already been reported when an
accurately estimated signal-to-signal ratio (SSR) is available. In
this paper, we approach the problem without estimating SSR.
We show that a simple method based on fusion of adapted
Gaussian mixture models and Kullback-Leibler divergence
calculated between models, achieves an accuracy of 97% and
93% when the two target speakers enlisted as three and two
most probable speakers, respectively.
Original language | English |
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Title of host publication | IEEE International Conference on Pattern Recognition (ICPR 2010) : Proceedings |
Publisher | IEEE Press |
Publication date | 2010 |
Pages | 4565-4568 |
ISBN (Electronic) | 978-0-7695-4109-9 |
DOIs | |
Publication status | Published - 2010 |
Event | 20 th International Conference on Pattern Recognition (ICPR) - Istanbul, Turkey Duration: 23 Aug 2010 → 26 Aug 2010 |
Conference
Conference | 20 th International Conference on Pattern Recognition (ICPR) |
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Country/Territory | Turkey |
City | Istanbul |
Period | 23/08/2010 → 26/08/2010 |
Series | Proceeding IEEE International Conference on Pattern Recognition (ICPR) |
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ISSN | 1051-4651 |