OLAC Record
oai:www.ldc.upenn.edu:LDC2019S20

Metadata
Title:2016 NIST Speaker Recognition Evaluation Test Set
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Greenberg, Craig, et al. 2016 NIST Speaker Recognition Evaluation Test Set LDC2019S20. Web Download. Philadelphia: Linguistic Data Consortium, 2019
Contributor:Greenberg, Craig
Sadjadi, Omid
Kheyrkhah, Timothee
Jones, Karen
Walker, Kevin
Strassel, Stephanie
Graff, David
Date (W3CDTF):2019
Date Issued (W3CDTF):2019-10-15
Description:*Introduction* 2016 NIST Speaker Recognition Evaluation Test Set was developed by the Linguistic Data Consortium (LDC) and NIST (National Institute of Standards and Technology). It contains approximately 340 hours of short segments of Tagalog, Cantonese, Cebuano and Mandarin telephone speech used as development and test data in the NIST-sponsored 2016 Speaker Recognition Evaluation (SRE). The ongoing series of SRE yearly evaluations conducted by NIST are intended to be of interest to researchers working on the general problem of text independent speaker recognition. To this end the evaluations are designed to be simple, to focus on core technology issues, to be fully supported and to be accessible to those wishing to participate. The SRE task is speaker detection, that is, to determine whether a specified target speaker is speaking during a given segment of speech. As in previous evaluations, SRE16 focused on telephone speech recorded over a variety of handset types for the training and test conditions. Further information about the evaluation, including some features added in SRE16, is contained in the evaluation plan included in this release. *Data* The telephone speech data was drawn from the Call My Net 2015 Corpus collected by LDC. Native speakers of Tagalog, Cantonese, Cebuano or Mandarin (220 unique speakers) made a total of ten telephone calls each, talking to people within their existing social networks. Speakers were encouraged to use different telephone instruments in a variety of acoustic settings and were instructed to talk for 8-10 minutes per call on a topic of their choice. All conversations were collected outside North America. Speech data is encoded as a-law, sampled at 8kHz, and stored in SPHERE formatted files. In addition to development and evaluation data, this corpus also contains trial lists, their associated keys, tables containing metadata information, and evaluation documentation. *Samples* Please view this speech sample. *Updates* None at this time.
Extent:Corpus size: 7217119 KB
Format:Sampling Rate: 8000
Sampling Format: alaw
Identifier:LDC2019S20
https://catalog.ldc.upenn.edu/LDC2019S20
ISBN: 1-58563-904-4
ISLRN: 261-271-974-389-4
Language:Tagalog
Yue Chinese
Cebuano
Mandarin Chinese
Language (ISO639):tgl
yue
ceb
cmn
License:LDC User Agreement for Non-Members: https://catalog.ldc.upenn.edu/license/LDC%20User%20Agreement%20for%20Non-Members.pdf
Medium:Distribution: Web Download
Publisher:Linguistic Data Consortium
Publisher (URI):https://www.ldc.upenn.edu
Relation (URI):https://catalog.ldc.upenn.edu/docs/LDC2019S20
Rights Holder:Portions © 2015, 2019 Trustees of the University of Pennsylvania
Type (DCMI):Sound
Type (OLAC):primary_text

OLAC Info

Archive:  The LDC Corpus Catalog
Description:  http://www.language-archives.org/archive/www.ldc.upenn.edu
GetRecord:  OAI-PMH request for OLAC format
GetRecord:  Pre-generated XML file

OAI Info

OaiIdentifier:  oai:www.ldc.upenn.edu:LDC2019S20
DateStamp:  2020-01-06
GetRecord:  OAI-PMH request for simple DC format

Search Info

Citation: Greenberg, Craig; Sadjadi, Omid; Kheyrkhah, Timothee; Jones, Karen; Walker, Kevin; Strassel, Stephanie; Graff, David. 2019. Linguistic Data Consortium.
Terms: area_Asia country_CN country_PH dcmi_Sound iso639_ceb iso639_cmn iso639_tgl iso639_yue olac_primary_text


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Up-to-date as of: Sat Jan 18 13:58:43 EST 2020