TY  - CONF
ID  - verdet10:interspeech
T1  - Channel Detectors for System Fusion in the Context of NIST LRE 2009
A1  - Verdet, Florian
A1  - Matrouf, Driss
A1  - Bonastre, Jean-François
A1  - Hennebert, Jean
TI  - Interspeech'2010
Y1  - 2010
CY  - Makuhari (Japan)
UR  - http://www.hennebert.org/download/publications/interspeech-2010_Channel-Detectors-for-System-Fusion-in-the-Context-of-NIST-LRE-2009.pdf
KW  - channel
KW  - channel category
KW  - channel detector
KW  - factor analysis
KW  - fusion
KW  - Language Identification
KW  - machine learning
N2  - One of the difficulties in Language Recognition is the variability of the speech signal due to speakers and channels. If channel mismatch is too big and when different categories of channels can be identified, one possibility is to build a separate language recognition system for each category and then to fuse them together. This article uses a system selector that takes, for each utterance, the scores of one of the channel-category dependent systems. This selection is guided by a channel detector. We analyze different ways to design such channel detectors: based on cepstral features or on the Factor Analysis channel variability term. The systems are evaluated in the context of NIST’s LRE 2009 and run at 1.65% minCavg for a subset of 8 languages and at 3.85% minCavg for the 23 language setup.
ER  -