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1
Spoken language recognition based on senone posteriors
In: https://www.sri.com/sites/default/files/publications/spoken_language_recognition_based_on_senone_posteriors.pdf (2014)
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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
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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4
SRI’s 2004 NIST speaker recognition evaluation system
In: http://www.speech.sri.com/papers/icassp2005-spkr-system.pdf (2005)
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5
SRI’s 2004 NIST speaker recognition evaluation system
In: http://www-speech.sri.com/papers/icassp2005-spkr-system.ps.gz (2005)
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6
Modeling NERFs for Speaker Recognition
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/odyssey2004-nerfs.ps.gz (2004)
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7
SVM Modeling of SNERF-Grams for Speaker Recognition
In: http://www.speech.sri.com/cgi-bin/run-distill?papers/icslp2004-snerfs.ps.gz (2004)
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8
Gadde, “Speaker recognition using prosodic and lexical features
In: http://www-speech.sri.com/papers/asru2003-spkrid.ps.gz (2003)
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9
Modeling Duration Patterns for Speaker Recognition
In: http://www-speech.sri.com/papers/eurospeech2003-spkrdur.ps.gz (2003)
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10
Gadde, “Speaker recognition using prosodic and lexical features
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/asru2003-spkrid.ps.gz (2003)
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11
Modeling duration patterns for speaker recognition," presented at Eurospeech
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/eurospeech2003-spkrdur.ps.gz (2003)
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12
Prosodic Knowledge Sources For Automatic Speech Recognition
In: http://www-speech.sri.com/papers/icassp2003-prosodyasr.ps.gz (2003)
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13
Training a prosody-based dialog act tagger from unlabeled data
In: http://www-speech.sri.com/cgi-bin/run-distill?ftp:papers/icassp2003-dialog.ps.gz (2003)
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14
Prosodic knowledge sources for automatic speech recognition
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2003-prosodyasr.ps.gz (2003)
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15
Training a Prosody-Based Dialog Act Tagger from Unlabeled Data
In: http://www-speech.sri.com/papers/icassp2003-dialog.ps.gz (2003)
Abstract: Dialog act tagging is an important step toward speech understanding, yet training such taggers usually requires large amounts of data labeled by linguistic experts. Here we investigate the use of unlabeled data for training HMM-based dialog act taggers. Three techniques are shown to be effective for bootstrapping a tagger from very small amounts of labeled data: iterative relabeling and retraining on unlabeled data; a dialog grammar to model dialog act context, and a model of the prosodic correlates of dialog acts. On the SPINE dialog corpus, the combined use of prosodic information and unlabeled data reduces the tagging error between 12% and 16%, compared to baseline systems using word information and various amounts of labeled data only.
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.8507
http://www-speech.sri.com/papers/icassp2003-dialog.ps.gz
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16
The SRI NIST 2008 speaker recognition evaluation system
In: https://www.sri.com/sites/default/files/publications/the_sri_nist_2008_speaker_recognition_evaluation_system.pdf
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17
Class-based score combination for speaker recognition
In: https://www.sri.com/sites/default/files/publications/class-dependent_score_combination_for_speaker_recog.pdf
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18
SRI’s 2004 NIST speaker recognition evaluation system
In: http://www-speech.sri.com/cgi-bin/run-distill?papers/icassp2005-spkr-system.ps.gz
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19
A COMPARISON OF APPROACHES FOR MODELING PROSODIC FEATURES IN SPEAKER RECOGNITION
In: http://www.speech.sri.com/cgi-bin/run-distill?papers/icassp2010-ferrer.ps.gz
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20
Adaptive and Discriminative Modeling for Improved Mispronunciation Detection
In: http://www.speech.sri.com/papers/Franco_Ferrer_Bratt_IS_ADEPT.pdf
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