IARPA Babel Javanese Language Pack IARPA-babel402b-v1.0b

Item Name: IARPA Babel Javanese Language Pack IARPA-babel402b-v1.0b
Author(s): Aric Bills, Thomas Conners, Anne David, Luanne Dela Cruz, Eyal Dubinski, Jonathan G. Fiscus, Ketty Gann, Mary Harper, Michael Kazi, Hanh Le, Nicolas Malyska, Jennifer Melot, Jessica Ray, Fred Richardson, Anton Rytting, Jacqui Zwanenburg
LDC Catalog No.: LDC2020S07
ISBN: 1-58563-937-0
ISLRN: 133-899-222-167-3
DOI: https://doi.org/10.35111/6N78-9C72
Release Date: July 15, 2020
Member Year(s): 2020
DCMI Type(s): Sound, Text
Sample Type: alaw
Sample Rate: 8000
Data Source(s): telephone conversations
Application(s): speech recognition
Language(s): Javanese
Language ID(s): jav
License(s): IARPA Babel Javanese Agreement (Not-For-Profit)
IARPA Babel Javanese Agreement (Non-Member)
IARPA Babel Javanese Agreement (For-Profit)
Online Documentation: LDC2020S07 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Bills, Aric, et al. IARPA Babel Javanese Language Pack IARPA-babel402b-v1.0b LDC2020S07. Web Download. Philadelphia: Linguistic Data Consortium, 2020.

Introduction

IARPA Babel Javanese Language Pack IARPA-babel402b-v1.0b was developed by Appen for the IARPA (Intelligence Advanced Research Projects Activity) Babel program. It contains approximately 204 hours of Javanese conversational and scripted telephone speech collected in 2014 and 2015 along with corresponding transcripts.

The Babel program focused on underserved languages and sought to develop speech recognition technology that could be rapidly applied to any human language to support keyword search performance over large amounts of recorded speech.

Data

The Javanese speech in this release represents the Central, Western, and Eastern Javanese dialect regions of Indonesia. 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 and 48kHz 24-bit PCM encoded audio in wav format.

Transcripts are encoded in UTF-8 in Latin script; they cover approximately 77% of the speech data. 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 this audio sample (SPH) and transcript sample (TXT).

Updates

None at this time.

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