IARPA Babel Cantonese Language Pack IARPA-babel101b-v0.4c

registration: 2016/08/17 13:28:17, last modified: 2017/05/18 09:00:00

title	IARPA Babel Cantonese Language Pack IARPA-babel101b-v0.4c
title.abbreviation
title.alternative
creator	developer Appen researcher Tony Andrus researcher Eyal Dubinski researcher Jonathan Fiscus researcher Breanna Gillies researcher Mary Harper researcher T. J. Hazen researcher Brook Hefright researcher Amy Jarrett researcher Willa Lin researcher Jessica Ray researcher Anton Rytting researcher Wade Shen researcher Evelyne Tzoukermann researcher Jamie Wong
subject	speech corpus
subject.linguisticField	applied_linguistics phonetics phonology
subject.monoMultilingual	monolingual
subject.resourceSubject	corpus
description	Introduction IARPA Babel Cantonese Language Pack IARPA-babel101b-v0.4c was developed by Appen for the IARPA (Intelligence Advanced Research Projects Activity) Babel program. It contains approximately 215 hours of Cantonese conversational and scripted telephone speech collected in 2011 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 Cantonese speech in this release represents that spoken in the Chinese provinces of Guangdong and Guangxi, and within those provinces, among five dialect groups. The gender distribution among speakers is approximately even; speakers' ages range from 16 years to 67 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. All audio data is presented as 8kHz 8-bit a-law encoded audio in sphere format. Transcripts are available in two versions: simplified Chinese characters and a romanization scheme based on the Yale system, both encoded in UTF-8. Further information about transcription methodology is contained in the documentation accompanying this release. Evaluation data is available from NIST in support of OpenKWS. Samples Please view the following samples: * audio sample * transcription * romanized transcription Updates None at this time.
description.price *This metadata is only as a guide
description.language	English
description.inputDevice	fixed_line_telephone mobile_phone
description.inputEnvironment	in_car noisy_condition streets and public places office_room
description.speakingStyle	spontaneous_speech
description.speechMode	dialogue
description.samplingRate	8 kHz
description.additionalData	analysis_parameter Chinese character transcription analysis_parameter Romanized transcription
publisher	Linguistic Data Consortium (LDC) https://www.ldc.upenn.edu
contributor	sponsor the IARPA (Intelligence Advanced Research Projects Activity) Babel program
contributor.attribute.author.motherTongue
contributor.attribute.author.dialect
contributor.attribute.author.level
contributor.attribute.author.age
contributor.attribute.author.gender
contributor.attribute.speaker.motherTongue	native
contributor.attribute.speaker.dialect	dialect standard_dialect
contributor.attribute.speaker.level
contributor.attribute.speaker.age	adult senior
contributor.attribute.speaker.gender	male female
contributor.attribute.speaker.number	approximately even gender distribution
date.created
date.issued	2016-07-19
date.modified
type	Sound Text
type.discourseType	interactive_discourse
type.linguisticType	primary_text
type.purpose	developing_technologies 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
type.style	speech
type.form	unfixed
type.sentence	long short
type.annotation
type.annotationSample
type.sample	audio sample: https://catalog.ldc.upenn.edu/desc/addenda/LDC2016S02.sph transcription: https://catalog.ldc.upenn.edu/desc/addenda/LDC2016S02.txt romanized transcription: https://catalog.ldc.upenn.edu/desc/addenda/LDC2016S02.rom.txt
format.extent	Corpus size: 6484312 KB approximately 215 hours of recording
format.medium	Web Download
format.encoding	UTF-8
format.markup
format.functionality
identifier	LDC2016S02 https://catalog.ldc.upenn.edu/LDC2016S02 ISBN:1-58563-746-7
identifier.doi
identifier.islrn	203-805-101-705-6
source
language	Yue Chinese
language.area	Asia
relation	hasVersion C-004923: IARPA Babel Assamese Language Pack IARPA-babel102b-v0.5a hasVersion C-004924: IARPA Babel Bengali Language Pack IARPA-babel103b-v0.4b hasVersion C-004930: IARPA Babel Pashto Language Pack IARPA-babel104b-v0.4bY hasVersion C-004932: IARPA Babel Turkish Language Pack IARPA-babel105b-v0.5 hasVersion C-004934: IARPA Babel Georgian Language Pack IARPA-babel404b-v1.0a hasVersion C-004938: IARPA Babel Tagalog Language Pack IARPA-babel106-v0.2g hasVersion C-004943: IARPA Babel Vietnamese Language Pack IARPA-babel107b-v0.7 hasVersion C-004950: IARPA Babel Haitian Creole Language Pack IARPA-babel201b-v0.2b hasVersion C-004977: IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d hasVersion C-005035: IARPA Babel Lao Language Pack IARPA-babel203b-v3.1a
relation.utilization *This metadata is automatically extracted
coverage.temporal	2011
coverage.spacial	Provinces of Guangdong and Guangxi, China
rights	Licensing Instructions for Subscription & Standard Members, and Non-Members: http://www.ldc.upenn.edu/language-resources/data/obtaining IARPA Babel Cantonese Agreement (Non-Member): https://catalog.ldc.upenn.edu/license/iarpa-babel-cantonese-agreement-non-member.pdf IARPA Babel Cantonese Agreement (Not-For-Profit): https://catalog.ldc.upenn.edu/license/iarpa-babel-cantonese-agreement-not-for-profit.pdf IARPA Babel Cantonese Agreement (For-Profit): https://catalog.ldc.upenn.edu/license/iarpa-babel-cantonese-agreement-for-profit.pdf Copyright: 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.

SHACHI - Language Resource Metadata Database

IARPA Babel Cantonese Language Pack IARPA-babel101b-v0.4c