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1
Addressee detection for dialog systems using temporal and spectral dimensions of speaking style,” in
In: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/paper-32.pdf (2013)
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2
The SRI NIST 2010 speaker recognition evaluation system
In: http://www.speech.sri.com/papers/icassp2011-sre10-system.pdf (2011)
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3
Effective Arabic Dialect Classification Using Diverse Phonotactic Models
In: http://www.icsi.berkeley.edu/pubs/speech/effectivearabic11.pdf (2011)
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4
Data-driven lexicon expansion for Mandarin broadcast news and conversation speech recognition
In: http://www.speech.sri.com/people/leixin/papers/LearnDict.pdf (2009)
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5
Exploiting user feedback for language model adaptation in meeting recognition
In: http://www.speech.sri.com/people/gokhan/pubs/ICASSP09_2.pdf (2009)
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6
S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
In: http://www.speech.sri.com/papers/eurospeech2007-lexical-sid.ps.gz (2007)
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7
S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
In: http://www.speech.sri.com/papers/IS07-gokhan-p1171.pdf (2007)
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8
S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
In: http://www.speech.sri.com/people/gokhan/pubs/IS072.pdf (2007)
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9
S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/eurospeech2007-lexical-sid.ps.gz (2007)
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10
Speaker recognition with session variability normalization based on MLLR adaptation transforms
In: http://www.icsi.berkeley.edu/pubs/speech/ieee-aslp2007-mllrsvm.ps.pdf (2007)
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11
Detecting categories in news video using acoustic, speech and image features
In: http://www.cs.berkeley.edu/~aberg/papers/trecvid06.pdf (2007)
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12
Combining prosodic, lexical and cepstral systems for deceptive speech detection
In: http://www.speech.sri.com/papers/icassp2006-deception.ps.gz (2006)
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13
Combining Prosodic, Lexical and Cepstral Systems for Deceptive Speech Detection
In: http://www.cs.columbia.edu/~julia/papers/icassp06_deception.pdf (2006)
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14
The contribution of cepstral and stylistic features to SRI’s 2005 NIST speaker recognition evaluation system
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2006-spkr-system.ps.gz (2006)
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15
Combining Prosodic, Lexical and Cepstral Systems for Deceptive Speech Detection
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2006-deception.ps.gz (2006)
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16
Combining prosodic, lexical and cepstral systems for deceptive speech detection
In: http://www.cs.columbia.edu/~frank/papers/icassp06_deception.pdf (2006)
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17
Does active learning help automatic dialog act taggin in meeting data
In: http://http.icsi.berkeley.edu/ftp/global/pub/speech/papers/eurospeech2005-active.pdf (2005)
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18
Does active learning help automatic dialog act taggin in meeting data
In: http://www.speech.sri.com/papers/eurospeech2005-active.ps.gz (2005)
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19
Distinguishing Deceptive from Non-Deceptive Speech
In: http://www.cs.columbia.edu/nlp/papers/2005/hirschberg_al_05.pdf (2005)
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20
Does active learning help automatic dialog act tagging in meeting data
In: http://www.hlt.utdallas.edu/~yangl/papers/interspeech05_da.pdf (2005)
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