IARPA Babel Guarani Language Pack IARPA-babel305b-v1.0c
|Item Name:||IARPA Babel Guarani Language Pack IARPA-babel305b-v1.0c|
|Author(s):||Lucy Andresen, Aric Bills, Judith Bishop, Claudia Brugman, Thomas Conners, Anne David, Eyal Dubinski, Jonathan G. Fiscus, Ketty Gann, Mary Harper, Michael Kazi, Hanh Le, Nicolas Malyska, Arlene Maurillo, Jennifer Melot, Shelley Paget, Jane Elizabeth Prebble, Jessica Ray, Fred Richardson, Anton Rytting, Sinney Shen|
|LDC Catalog No.:||LDC2019S08|
|Release Date:||May 15, 2019|
|DCMI Type(s):||Sound, Text|
|Data Source(s):||telephone conversations|
IARPA Babel Guarani Agreement (For-Profit)
IARPA Babel Guarani Agreement (Non-Member)
IARPA Babel Guarani Agreement (Not-For-Profit)
|Online Documentation:||LDC2019S08 Documents|
|Licensing Instructions:||Subscription & Standard Members, and Non-Members|
|Citation:||Andresen, Lucy, et al. IARPA Babel Guarani Language Pack IARPA-babel305b-v1.0c LDC2019S08. Web Download. Philadelphia: Linguistic Data Consortium, 2019.|
IARPA Babel Guarani Language Pack IARPA-babel305b-v1.0c was developed by Appen for the IARPA (Intelligence Advanced Research Projects Activity) Babel program. It contains approximately 198 hours of Guarani conversational and scripted telephone speech collected in 2014 and 2015 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 Guarani speech in this release represents that spoken in Paraguay. The gender distribution among speakers is approximately equal; 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.
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. Further information about transcription methodology is contained in the documentation accompanying this release.
None at this time.