IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d

Item Name: IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d
Author(s): Jess Andresen, Aric Bills, Judith Bishop, Thomas Conners, Eyal Dubinski, Jonathan G. Fiscus, Mary Harper, Kirill Kozlov, Nicolas Malyska, Jennifer Melot, Michelle Morrison, Josh Phillips, Jessica Ray, Anton Rytting, Wade Shen, Ronnie Silber, Evelyne Tzoukermann, Jamie Wong
LDC Catalog No.: LDC2017S05
ISBN: 1-58563-790-4
ISLRN: 874-256-867-958-7
DOI: https://doi.org/10.35111/afrp-a637
Release Date: March 17, 2017
Member Year(s): 2017
DCMI Type(s): Sound, Text
Sample Type: a-law
Sample Rate: 8000
Data Source(s): telephone conversations
Application(s): speech recognition
Language(s): Swahili
Language ID(s): swa
License(s): IARPA Babel Swahili Agreement (For-Profit)
IARPA Babel Swahili Agreement (Non-Member)
IARPA Babel Swahili Agreement (Not-For-Profit)
Online Documentation: LDC2017S05 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Andresen, Jess, et al. IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d LDC2017S05. Web Download. Philadelphia: Linguistic Data Consortium, 2017.
Related Works: View


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.


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.


Please view this speech sample and transcript sample.


None at this time.

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