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Addressee detection for dialog systems using temporal and spectral dimensions of speaking style,” in
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In: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/paper-32.pdf (2013)
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Pitch-gesture modeling using subband autocorrelation change detection
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In: http://www.slaney.org/malcolm/Microsoft/Slaney2013%28ToneWithoutPitch%29.pdf (2013)
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The SRI NIST 2010 speaker recognition evaluation system
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In: http://www.speech.sri.com/papers/icassp2011-sre10-system.pdf (2011)
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Comparing the contributions of context and prosody in text-independent dialog act recognition
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In: http://www.cs.cmu.edu/~kornel/pubs/0005374.pdf (2010)
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S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
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In: http://www.speech.sri.com/papers/eurospeech2007-lexical-sid.ps.gz (2007)
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S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
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In: http://www.speech.sri.com/papers/IS07-gokhan-p1171.pdf (2007)
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S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
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In: http://www.speech.sri.com/people/gokhan/pubs/IS072.pdf (2007)
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Crossgenre feature comparisons for spoken sentence segmentation
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In: http://pageperso.lif.univ-mrs.fr/%7Ebenoit.favre/papers/favre_ijsc2007.pdf (2007)
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S.: Duration and Pronunciation Conditioned Lexical Modeling for Speaker Verification
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In: http://www-speech.sri.com/cgi-bin/run-distill?papers/eurospeech2007-lexical-sid.ps.gz (2007)
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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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Higher-Level Features in Speaker Recognition,” in Speaker Classification I
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In: http://www.speech.sri.com/papers/bookchapter-hlf-LNAI07.pdf (2007)
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Combining prosodic, lexical and cepstral systems for deceptive speech detection
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In: http://www.speech.sri.com/papers/icassp2006-deception.ps.gz (2006)
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Using Prosody for Automatic Sentence Segmentation of Multi-Party Meetings
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In: http://www.mde.zcu.cz/data/Kolar06tsd.pdf (2006)
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Abstract:
We explore the use of prosodic features beyond pauses, including duration, pitch, and energy features, for automatic sentence segmentation of ICSI meeting data. We examine two different approaches to boundary classification: score-level combination of independent language and prosodic models using HMMs, and feature-level combination of models using a boosting-based method (BoosTexter). We report classification results for reference word transcripts as well as for transcripts from a state-of-the-art automatic speech recognizer (ASR). We also compare results using the lexical model plus a pause-only prosody model, versus results using additional prosodic features. Results show that (1) information from pauses is important, including pause duration both at the boundary and at the previous and following word boundaries; (2) adding duration, pitch, and energy features yields significant improvement over pause alone; (3) the integrated boosting-based model performs better than the HMM for ASR conditions; (4) training the boosting-based model on recognized words yields further improvement.
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.7600 http://www.mde.zcu.cz/data/Kolar06tsd.pdf
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Combining Prosodic, Lexical and Cepstral Systems for Deceptive Speech Detection
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In: http://www.cs.columbia.edu/~julia/papers/icassp06_deception.pdf (2006)
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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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Combining Prosodic, Lexical and Cepstral Systems for Deceptive Speech Detection
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In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2006-deception.ps.gz (2006)
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Combining prosodic, lexical and cepstral systems for deceptive speech detection
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In: http://www.cs.columbia.edu/~frank/papers/icassp06_deception.pdf (2006)
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Does active learning help automatic dialog act taggin in meeting data
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In: http://http.icsi.berkeley.edu/ftp/global/pub/speech/papers/eurospeech2005-active.pdf (2005)
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Does active learning help automatic dialog act taggin in meeting data
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In: http://www.speech.sri.com/papers/eurospeech2005-active.ps.gz (2005)
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Automatic Dialog Act Segmentation and Classification in Multiparty Meetings
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In: http://www.icsi.berkeley.edu/~yangl/icassp2005-da-seg-class.pdf (2005)
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