In this newsletter: LDC data and commercial technology development New publications: L2-KSU Native and Non-Native Arabic Speech<https://catalog.ldc.upenn.edu/LDC2024S11> MATERIAL Somali-English Language Pack<https://catalog.ldc.upenn.edu/LDC2024S10>
________________________________ LDC data and commercial technology development For-profit organizations are reminded that an LDC membership is a pre-requisite for obtaining a commercial license to almost all LDC databases. Non-member organizations, including non-member for-profit organizations, cannot use LDC data to develop or test products for commercialization, nor can they use LDC data in any commercial product, or for any commercial purpose. LDC data users should consult corpus-specific license agreements for limitations on the use of certain corpora. Visit the Licensing<https://www.ldc.upenn.edu/data-management/using/licensing> page for further information. ________________________________ New publications: L2-KSU Native and Non-Native Arabic Speech<https://catalog.ldc.upenn.edu/LDC2024S11> was developed by King Saud University<http://ksu.edu.sa/en/> (KSU) and contains approximately six hours of Modern Standard Arabic read speech from 80 subjects, along with transcripts and speaker metadata. The speech data was collected in 2022 from 40 native and 40 non-native speakers. Native speakers were from Saudi Arabia, Egypt, and Palestine, and provided audio recordings through the crowd sourcing platform Khamsat<https://khamsat.com/>. Non-native speakers were Central and West African students enrolled in KSU's Arabic Linguistics Institute; they provided speech recordings on site. All subjects read a series of ten sentences, repeating each sentence multiple times. 2024 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee. * MATERIAL Somali-English Language Pack<https://catalog.ldc.upenn.edu/LDC2024S10> was developed by Appen<http://www.appen.com/> for the IARPA (Intelligence Advanced Research Projects Activity) MATERIAL<https://www.iarpa.gov/index.php/research-programs/material> (Machine Translation for English Retrieval of Information in Any Language) program. It contains 80 hours of Somali conversational telephone speech, transcripts, English translations, annotations, and queries. Calls were made using different telephones (e.g., mobile, landline) from a variety of environments. Transcripts cover approximately 10% of the speech files, and approximately 4% of the speech files were translated into English. This release also includes domain annotations, English queries, and their relevance annotations. The MATERIAL program focused on underserved languages with the ultimate goal to build cross language information retrieval systems to find speech and text content using English search queries. 2024 members can access this corpus through their LDC accounts provided they have submitted a completed copy of the special license agreement. Non-members may license this data for a fee. To unsubscribe from this newsletter, log in to your LDC account<https://catalog.ldc.upenn.edu/login> and uncheck the box next to "Receive Newsletter" under Account Options or contact LDC for assistance. Membership Coordinator Linguistic Data Consortium<ldc.upenn.edu> University of Pennsylvania T: +1-215-573-1275 E: [email protected]<mailto:[email protected]> M: 3600 Market St. Suite 810 Philadelphia, PA 19104
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