OLAC Record
oai:www.ldc.upenn.edu:LDC2017S05

Metadata
Title:IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d
Access Rights:Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining
Bibliographic Citation:Andresen, Jess, et al. IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d LDC2017S05. Web Download. Philadelphia: Linguistic Data Consortium, 2017
Contributor:Andresen, Jess
Bills, Aric
Conners, Thomas
Dubinski, Eyal
Fiscus, Jonathan G.
Harper, Mary
Kozlov, Kirill
Malyska, Nicolas
Melot, Jennifer
Morrison, Michelle
Phillips, Josh
Ray, Jessica
Rytting, Anton
Shen, Wade
Silber, Ronnie
Tzoukermann, Evelyne
Wong, Jamie
Date (W3CDTF):2017
Date Issued (W3CDTF):2017-03-17
Description:*Introduction* IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d was developed by Appen for the IARPA (Intelligence Advanced Research Projects Activity) Babel program. It contains approximately 350 hours of Swahili conversational and scripted telephone speech collected from 2012-2014 along with corresponding transcripts. The Babel program focuses on underserved languages and seeks to develop speech recognition technology that can be rapidly applied to any human language to support keyword search performance over large amounts of recorded speech. *Data* The Swahili speech in this release represents that spoken in the Nairobi dialect region of Kenya. The gender distribution among speakers is approximately equal; speakers' ages range from 16 years to 65 years. Calls were made using different telephones (e.g., mobile, landline) from a variety of environments including the street, a home or office, a public place, and inside a vehicle. Audio data is presented as 8kHz 8-bit a-law encoded audio in sphere format or 48kHz 24-bit PCM encoded audio in wav format. Transcripts are encoded in UTF-8. Further information about transcription methodology is contained in the documentation accompanying this release. Additional evaluation data is available from NIST in support of OpenKWS. *Samples* Please view this speech sample and transcript sample. *Updates* None at this time.
Extent:Corpus size: 11838904 KB
Format:Sampling Rate: 8000
Sampling Format: a-law
Identifier:LDC2017S05
https://catalog.ldc.upenn.edu/LDC2017S05
ISBN: 1-58563-790-4
ISLRN: 874-256-867-958-7
Language:Swahili (individual language)
Swahili (macrolanguage); Swahili
Language (ISO639):swh
swa
License:IARPA Babel Swahili Agreement (Not-For-Profit): https://catalog.ldc.upenn.edu/license/IARPA%20Babel%20Swahili%20Agreement%20(Not-For-Profit).pdf
IARPA Babel Swahili Agreement (For-Profit): https://catalog.ldc.upenn.edu/license/IARPA%20Babel%20Swahili%20Agreement%20(For-Profit).pdf
IARPA Babel Swahili Agreement (Non-Member): https://catalog.ldc.upenn.edu/license/IARPA%20Babel%20Swahili%20Agreement%20(Non-Member).pdf
Medium:Distribution: Web Download
Publisher:Linguistic Data Consortium
Publisher (URI):https://www.ldc.upenn.edu
Relation (URI):https://catalog.ldc.upenn.edu/docs/LDC2017S05
Rights Holder:Portions © 2015 U.S. Government

The U.S. Government acquired this data from Appen Pty Ltd, which assigned the copyright to the data to the U.S. Government.
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:LDC2017S05
DateStamp:  2019-12-18
GetRecord:  OAI-PMH request for simple DC format

Search Info

Citation: Andresen, Jess; Bills, Aric; Conners, Thomas; Dubinski, Eyal; Fiscus, Jonathan G.; Harper, Mary; Kozlov, Kirill; Malyska, Nicolas; Melot, Jennifer; Morrison, Michelle; Phillips, Josh; Ray, Jessica; Rytting, Anton; Shen, Wade; Silber, Ronnie; Tzoukermann, Evelyne; Wong, Jamie. 2017. Linguistic Data Consortium.
Terms: area_Africa country_TZ dcmi_Sound dcmi_Text iso639_swa iso639_swh olac_primary_text


http://www.language-archives.org/item.php/oai:www.ldc.upenn.edu:LDC2017S05
Up-to-date as of: Sat Jan 18 13:58:15 EST 2020