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2011 NIST Language Recognition Evaluation Test Set
Greenberg, Craig; Martin, Alvin; Graff, David. - : Linguistic Data Consortium, 2018. : https://www.ldc.upenn.edu, 2018
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2011 NIST Language Recognition Evaluation Test Set ...
Greenberg, Craig; Martin, Alvin; Graff, David. - : Linguistic Data Consortium, 2018
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2010 NIST Speaker Recognition Evaluation Test Set
Greenberg, Craig; Martin, Alvin; Graff, David. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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2010 NIST Speaker Recognition Evaluation Test Set ...
Greenberg, Craig; Martin, Alvin; Graff, David. - : Linguistic Data Consortium, 2017
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2009 NIST Language Recognition Evaluation Test Set
Martin, Alvin; Greenberg, Craig; Graff, David. - : Linguistic Data Consortium, 2014. : https://www.ldc.upenn.edu, 2014
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2009 NIST Language Recognition Evaluation Test Set ...
Martin, Alvin; Greenberg, Craig; Graff, David. - : Linguistic Data Consortium, 2014
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2007 NIST Language Recognition Evaluation Test Set
Martin, Alvin; Le, Audrey. - : Linguistic Data Consortium, 2009. : https://www.ldc.upenn.edu, 2009
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8
2007 NIST Language Recognition Evaluation Supplemental Training Set
Martin, Alvin; Le, Audrey; Graff, David; van Santen, Jan. - : Linguistic Data Consortium, 2009. : https://www.ldc.upenn.edu, 2009
Abstract: *Introduction* 2007 NIST Language Recognition Evaluation Supplemental Training Set was developed by the Linguistic Data Consortium (LDC) and the National Institute of Standards and Technology (NIST). It consists of 118 hours of conversational telephone speech segments in the following languages and dialects: Arabic (Egyptian colloquial), Bengali, Min Nan Chinese, Wu Chinese, Taiwan Mandarin, Cantonese, Russian, Mexican Spanish, Thai, Urdu, and Tamil. The goal of NIST's Language Recognition Evaluation (LRE) is to establish the baseline of current performance capability for language recognition of conversational telephone speech and to lay the groundwork for further research efforts in the field. NIST conducted three previous language recognition evaluations, in 1996, 2003 and 2005. The most significant differences between those evaluations and the 2007 task were the increased number of languages and dialects, the greater emphasis on a basic detection task for evaluation and the variety of evaluation conditions. Thus, in 2007, given a segment of speech and a language of interest to be detected (i.e., a target language), the task was to decide whether that target language was in fact spoken in the given telephone speech segment (yes or no), based on an automated analysis of the data contained in the segment. *Data* The supplemental training material in this release consists of the following: * Approximately 53 hours of conversational telephone speech segments in Arabic (Egyptian colloquial), Bengali, Cantonese, Min Nan Chinese, Wu Chinese, Russian, Thai, and Urdu. This material is taken from LDC's CALLHOME, CALLFRIEND, and Mixer collections. * Approximately 65 hours of full telephone conversations in Mandarin Chinese (Taiwan), Spanish (Mexican), and Tamil. This material was collected by Oregon Health and Science University (OHSU), Beaverton, Oregon. The test segments used in the 2005 NIST Language Recognition Evaluation (LDC2008S05) were derived from these full conversations. In addition to the supplemental material contained in this release, the training data for the 2007 NIST Language Recognition Evaluation (LDC2009S04) consisted of data from previous LRE evaluation test sets, namely, 2003 NIST Language Recognition Evaluation (LDC2006S31) and 2005 NIST Language Recognition Evaluation (LDC2008S05). LDC released other LREs as: * 2003 NIST Language Recognition Evaluation (LDC2006S31) * 2005 NIST Language Recognition Evaluation (LDC2008S05) * 2007 NIST Language Recognition Evaluation (LDC2009S04) * 2009 NIST Language Recognition Evaluation Test Set (LDC2014S06) * 2011 NIST Language Recognition Evaluation Test Set (LDC2018S06) *Samples* For an example of the data in this corpus, please listen to this Egyptian Arabic sample (WAV) from the data set. *Updates* None at this time.
URL: https://catalog.ldc.upenn.edu/LDC2009S05
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2007 NIST Language Recognition Evaluation Supplemental Training Set ...
Martin, Alvin; Le, Audrey; Graff, David. - : Linguistic Data Consortium, 2009
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2007 NIST Language Recognition Evaluation Test Set ...
Martin, Alvin; Le, Audrey. - : Linguistic Data Consortium, 2009
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11
2005 NIST Language Recognition Evaluation
Le, Audrey; Martin, Alvin; Hadfield, Hannah. - : Linguistic Data Consortium, 2008. : https://www.ldc.upenn.edu, 2008
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2005 NIST Language Recognition Evaluation ...
Le, Audrey; Martin, Alvin; Hadfield, Hannah. - : Linguistic Data Consortium, 2008
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13
NIST speaker recognition evaluations utilizing the Mixer Corpora - 2004, 2005, 2006
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 15 (2007) 7, 1951-1959
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2004 Spring NIST Rich Transcription (RT-04S) Development Data
Fiscus, Jonathan G.; Garofolo, John S.; Le, Audrey. - : Linguistic Data Consortium, 2007. : https://www.ldc.upenn.edu, 2007
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2004 Spring NIST Rich Transcription (RT-04S) Evaluation Data
Fiscus, Jonathan G.; Garofolo, John S.; Le, Audrey. - : Linguistic Data Consortium, 2007. : https://www.ldc.upenn.edu, 2007
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2004 Spring NIST Rich Transcription (RT-04S) Development Data ...
Fiscus, Jonathan G.; Garofolo, John S.; Le, Audrey. - : Linguistic Data Consortium, 2007
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2004 Spring NIST Rich Transcription (RT-04S) Evaluation Data ...
Fiscus, Jonathan G.; Garofolo, John S.; Le, Audrey. - : Linguistic Data Consortium, 2007
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18
NIST and NFI-TNO evaluations of automatic speaker recognition
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 20 (2006) 2-3, 128-158
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2003 NIST Language Recognition Evaluation
Martin, Alvin; Pryzbocki, Mark. - : Linguistic Data Consortium, 2006. : https://www.ldc.upenn.edu, 2006
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2004 NIST Speaker Recognition Evaluation
Martin, Alvin; Przybocki, Mark. - : Linguistic Data Consortium, 2006. : https://www.ldc.upenn.edu, 2006
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