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Speaker recognition with session variability normalization based on MLLR adaptation transforms
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In: http://www.icsi.berkeley.edu/pubs/speech/ieee-aslp2007-mllrsvm.ps.pdf (2007)
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The contribution of cepstral and stylistic features to SRI’s 2005 NIST speaker recognition evaluation system
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In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2006-spkr-system.ps.gz (2006)
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SRI’s 2004 NIST speaker recognition evaluation system
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In: http://www.speech.sri.com/papers/icassp2005-spkr-system.pdf (2005)
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SRI’s 2004 NIST speaker recognition evaluation system
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In: http://www-speech.sri.com/papers/icassp2005-spkr-system.ps.gz (2005)
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The SRI NIST 2008 speaker recognition evaluation system
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In: https://www.sri.com/sites/default/files/publications/the_sri_nist_2008_speaker_recognition_evaluation_system.pdf
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SRI’s 2004 NIST speaker recognition evaluation system
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In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2005-spkr-system.ps.gz
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ISCA Archive Speaker Verification Based on Broad Phonetic Categories
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In: http://isca-speech.org/archive_open/archive_papers/odyssey/odys_201.pdf
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ACROSS-PHONE VARIABILITY AND DIAGONAL TERM IN JOINT FACTOR ANALYSIS FOR SPEAKER RECOGNITION
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In: http://www.speech.sri.com/papers/icassp2010-phone-jfa.pdf
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NAP AND WCCN: COMPARISON OF APPROACHES USING MLLR-SVM SPEAKER VERIFICATION SYSTEM
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In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2007-nap-wccn.ps.gz
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Abstract:
We compare two recently proposed techniques, within class covariance normalization (WCCN) [1] and nuisance attribute projection (NAP) [2], for intersession variability compensation in speaker verification. The comparison is performed using an MLLR-SVM speaker verification system. Both techniques model intersession variability using a within-speaker covariance matrix (WSCM). However, they manipulate eigenvectors of this matrix differently. We compare them on the 2005 and 2006 NIST speaker recognition evaluation (SRE) task. Results show that WCCN is more sensitive to the choice of background speakers and NAP is more sensitive to the choice of data for WSCM estimation. WCCN gives the best performance on 2005 SRE. On 2006 SRE, both techniques give similar performance under matched conditions. Further experiments with a simple combination of these techniques show slight improvements in the best performance of either technique. Overall results show that an MLLR-SVM system with either NAP or WCCN performs comparably to the best single systems in the 2006 NIST SRE. Index Terms — Speaker recognition, Intersession variability, MLLR transforms, SVM
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.2799
http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2007-nap-wccn.ps.gz
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NAP AND WCCN: COMPARISON OF APPROACHES USING MLLR-SVM SPEAKER VERIFICATION SYSTEM
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In: http://www.speech.sri.com/papers/icassp2007-nap-wccn.ps.gz
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