OLAC Record
oai:www.ldc.upenn.edu:LDC2021S03

Metadata
Title:Global TIMIT Mandarin Chinese
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Ding, Hongwei, et al. Global TIMIT Mandarin Chinese LDC2021S03. Web Download. Philadelphia: Linguistic Data Consortium, 2021
Contributor:Ding, Hongwei
Liao, Sishi
Zhan, Yuqing
Yuan, Jiahong
Liberman, Mark
Date (W3CDTF):2021
Date Issued (W3CDTF):2021-03-15
Description:*Introduction* Global TIMIT Mandarin Chinese was developed by the Linguistic Data Consortium and Shanghai Jiao Tong University and consists of approximately five hours of read speech and transcripts in Mandarin Chinese. The Global TIMIT project aimed to create a series of corpora in a variety of languages with a similar set of key features as in the original TIMIT Acoustic-Phonetic Continuous Speech Corpus (LDC93S1) which was designed for acoustic-phonetic studies and for the development and evaluation of automatic speech recognition systems. Specifically, these features included: * A large number of fluently-read sentences, containing a representative sample of phonetic, lexical, syntactic, semantic, and pragmatic patterns * A relatively large number of speakers * Time-aligned lexical and phonetic transcription of all utterances * Some sentences read by all speakers, others read by a few speakers, and others read by just one speaker *Data* Global TIMIT Mandarin Chinese consists of 50 speakers reading 120 sentences selected from Chinese Gigaword Fifth Edition (LDC2011T13). Among the 120 sentences, 20 sentences were read by all speakers, 40 sentences were read by 10 speakers, and 60 sentences were read by one speaker, for a total of 3220 sentence types. The corpus was recorded at Shanghai Jiao Tong University, China. Speakers (25 female, 25 male) were students at the university and all achieved Class 2 Level 1 or better on Putonghua Shuiping Ceshi (the national standard Mandarin proficiency test). All speech data are presented as 16kHz, 16-bit flac compressed wav files. Each file has accompanying phone and word segmentation files, as well as Praat TextGrid files. *Sponsorship* The authors acknowledge the generous support of the University of Pennsylvania's Office of the Vice Provost for Global Initiatives (PennGlobal) through its Penn China Research and Engagement Fund, and the School of Arts and Sciences through its Global Engagement Fund as well as the Linguistic Data Consortium. *Samples* Please view the following samples: * Audio (FLAC) * Word (TXT) * Phones (TXT) * TextGrid (TXT) *Updates* None at this time.
Extent:Corpus size: 571920 KB
Format:Sampling Rate: 16000
Sampling Format: pcm
Identifier:LDC2021S03
https://catalog.ldc.upenn.edu/LDC2021S03
ISBN: 1-58563-959-1
ISLRN: 698-533-540-909-9
DOI: 10.35111/bvxn-eh36
Language:Mandarin Chinese
Language (ISO639):cmn
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/LDC2021S03
Rights Holder:Portions © 2000-2010 Agence France Presse, © 1991-2010 Central News Agency (Taiwan), © 2006-2010 China Military Online, © 2006-2010 Chinanews.com, © 2006-2010 Guangming Daily, © 2006-2010 Peoples Daily, © 1998, 2000-2003 SPH AsiaOne, Ltd., © 1990-2010 Xinhua News Agency, © 2003, 2005, 2007, 2009, 2011, 2021 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
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OAI Info

OaiIdentifier:  oai:www.ldc.upenn.edu:LDC2021S03
DateStamp:  2022-12-12
GetRecord:  OAI-PMH request for simple DC format

Search Info

Citation: Ding, Hongwei; Liao, Sishi; Zhan, Yuqing; Yuan, Jiahong; Liberman, Mark. 2021. Linguistic Data Consortium.
Terms: area_Asia country_CN dcmi_Sound dcmi_Text iso639_cmn olac_primary_text


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