oai:www.ldc.upenn.edu:LDC2022S10
| |
OLAC Record oai:www.ldc.upenn.edu:LDC2022S10 |
| Metadata | ||
| Title: | 2017 NIST Language Recognition Evaluation Training and Development Sets | |
| 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. 2017 NIST Language Recognition Evaluation Training and Development Sets LDC2022S10. Web Download. Philadelphia: Linguistic Data Consortium, 2022 | |
| Contributor: | Greenberg, Craig | |
| Sadjadi, Omid | ||
| Reynolds, Douglas | ||
| Singer, Elliot | ||
| Graff, David | ||
| Date (W3CDTF): | 2022 | |
| Date Issued (W3CDTF): | 2022-10-17 | |
| Description: | *Introduction* 2017 NIST Language Recognition Evaluation Training and Development Sets contains training and development material for the 2017 NIST Language Recognition Evaluation. It consists of approximately 2,100 hours of conversational telephone speech, broadcast conversation, broadcast narrow band speech, and speech from video in the following 14 languages, dialects, and varieties: Arabic (Iraqi, Levantine, Maghrebi, Egyptian), English (British, American), Polish, Russian, Portuguese (Brazilian), Spanish (Caribbean, European, Latin American Continental), and Chinese (Mandarin, Min Nan). The goal of the NIST (National Institute of Standards and Technology) 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 language recognition evaluations in 1996, 2003, 2005, 2007, 2009, 2011, and 2015. The 2017 evaluation focused on differentiating closely related language pairs. In addition to conversational telephone speech, broadcast conversation, and broadcast narrow band speech, speech excerpts extracted from video data were used. Further information regarding this evaluation can be found in the evaluation plan which is also included in the documentation for this release. LDC released the prior LREs as: * 2003 NIST Language Recognition Evaluation (LDC2006S31) * 2005 NIST Language Recognition Evaluation (LDC2008S05) * 2007 NIST Language Recognition Evaluation Test Set (LDC2009S04) * 2007 NIST Language Recognition Evaluation Supplemental Training Set (LDC2009S05) * 2009 NIST Language Recognition Evaluation Test Set (LDC2014S06) * 2011 NIST Language Recognition Evaluation Test Set (LDC2018S06) *Data* This release includes data from LDC's CALLFRIEND and Fisher telephone collections, the VAST video collection, various broadcast sources and earlier NIST LRE test sets. The training audio files are single-channel, 8-KHz sample rate in NIST SPHERE format, either mu-law, A-law or 16-bit PCM. The development audio files are also single-channel, but vary in format: either SPHERE or FLAC-compressed MSWAV (RIFF). All "*.flac" files are 16-bit PCM, 44.1 KHz sample rate; the "*.sph" files are all 8-KHz, with either mu-law or 16-bit PCM samples. *Samples* Please view the following audio sample. *Updates* None at this time. | |
| Extent: | Corpus size: 65699443 KB | |
| Format: | Sampling Rate: 8000, 44100 | |
| Sampling Format: PCM, u-law, a-law | ||
| Identifier: | LDC2022S10 | |
| https://catalog.ldc.upenn.edu/LDC2022S10 | ||
| ISBN: 1-58563-999-0 | ||
| ISLRN: 854-427-979-036-7 | ||
| DOI: 10.35111/awny-7397 | ||
| Language: | Arabic | |
| English | ||
| Polish | ||
| Russian | ||
| Portuguese | ||
| Spanish | ||
| Mandarin Chinese | ||
| Min Nan Chinese | ||
| Language (ISO639): | ara | |
| eng | ||
| pol | ||
| rus | ||
| por | ||
| spa | ||
| cmn | ||
| nan | ||
| License: | LDC User Agreement for Non-Members: https://catalog.ldc.upenn.edu/license/ldc-non-members-agreement.pdf | |
| Medium: | Distribution: Web Download | |
| Publisher: | Linguistic Data Consortium | |
| Publisher (URI): | https://www.ldc.upenn.edu | |
| Relation (URI): | https://catalog.ldc.upenn.edu/docs/LDC2022S10 | |
| Rights Holder: | Portions © 2013-2014 Agora Radio Group, © 2013 BBC, © 2013 Bethel Church of Redding, © 2013 BFBS, © 2013 Blago Foundation, © 2013 Brazil Communication Company, © 2010-2011 Cable News Network, LP, LLLP, © 2013 El Pando Zambrano.com, © 2013-2014 Global, © 2010-2011 New Tang Dynasty TV, © 2010-2011 Phoenix New Media Limited, © 2013 Radio Amistad, C.por A., © 2013 Radio UNAL, © 2013 Spanish Radio and Television Corporation, © 2013 The New Television of the South CA (TVSUR), © 2013 University of Puerto Rico Radio Network, © 2010 WorldNetCast/TVNET, © 2011-2018 You Tube, LLC, © 1996-1999, 2001-2011, 2013-2014, 2018, 2022 Trustees of the University of Pennsylvania | |
| Type (DCMI): | Sound | |
| Text | ||
| 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:LDC2022S10 | |
| DateStamp: | 2023-11-03 | |
| GetRecord: | OAI-PMH request for simple DC format | |
Search Info | ||
| Citation: | Greenberg, Craig; Sadjadi, Omid; Reynolds, Douglas; Singer, Elliot; Graff, David. 2022. Linguistic Data Consortium. | |
| Terms: | area_Asia area_Europe country_CN country_ES country_GB country_PL country_PT country_RU dcmi_Sound dcmi_Text iso639_ara iso639_cmn iso639_eng iso639_nan iso639_pol iso639_por iso639_rus iso639_spa olac_primary_text | |