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ISCApad Archive » 2017 » ISCApad #226 » Resources » Database » Linguistic Data Consortium (LDC) update (March 2017) |
ISCApad #226 |
Saturday, April 08, 2017 by Chris Wellekens |
In this newsletter: BOLT Chinese Discussion Forum Parallel Training Data IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d GALE English-Chinese Parallel Aligned Treebank -- Training New Corpora (1) BOLT Chinese Discussion Forum Parallel Training Data was developed by LDC and consists of 1,876,799 tokens of Chinese discussion forum data collected for the DARPA BOLT program along with their corresponding English translations. The BOLT (Broad Operational Language Translation) program developed machine translation and information retrieval for less formal genres, focusing particularly on user-generated content. LDC supported the BOLT program by collecting informal data sources -- discussion forums, text messaging and chat -- in Chinese, Egyptian Arabic and English. The collected data was translated and annotated for various tasks including word alignment, treebanking, propbanking and co-reference. The source data in this release consists of discussion forum threads harvested from the Internet by LDC using a combination of manual and automatic processes. The full source data collection is released as BOLT Chinese Discussion Forums (LDC2016T05). Word-aligned and tagged data is released as BOLT Chinese-English Word Alignment and Tagging - Discussion Forum Training (LDC2016T19). BOLT Chinese Discussion Forum Parallel Training Data is distributed via web download.
2017 Subscription Members will automatically receive copies of this corpus. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $1750. * (2) 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 200 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.
Transcripts are encoded in UTF-8.
IARPA Babel Swahili Language Pack IARPA-babel202b-v1.0d is distributed via web download.
2017 Subscription Members will receive copies of this corpus provided they have submitted a completed copy of the special license agreement. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $25. * (3) Noisy TIMIT Speech was developed by the Florida Institute of Technology and contains approximately 322 hours of speech from the TIMIT Acoustic-Phonetic Continuous Speech Corpus (LDC93S1) modified with different additive noise levels. Only the audio has been modified; the original arrangement of the TIMIT corpus is still as described by the TIMIT documentation. The additive noise are white, pink, blue, red, violet and babble noise with levels varying in 5 dB (decibel) steps, ranging from 5 to 50 dB. The color noise types were generated artificially using MATLAB. The babble noise was selected from a random segment of recorded babble speech scaled relative to the power of the original TIMIT audio signal. Noisy TIMIT Speech is distributed via web download.
2017 Subscription Members will automatically receive copies of this corpus. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $400. * (4) GALE English-Chinese Parallel Aligned Treebank -- Training was developed by LDC and contains 196,123 tokens of word aligned English and Chinese parallel text with treebank annotations. This material was used as training data in the DARPA GALE (Global Autonomous Language Exploitation) program. Parallel aligned treebanks are treebanks annotated with morphological and syntactic structures aligned at the sentence level and the sub-sentence level. Such data sets are useful for natural language processing and related fields, including automatic word alignment system training and evaluation, transfer-rule extraction, word sense disambiguation, translation lexicon extraction and cultural heritage and cross-linguistic studies. With respect to machine translation system development, parallel aligned treebanks may improve system performance with enhanced syntactic parsers, better rules and knowledge about language pairs and reduced word error rate. The English source data was translated into Chinese. Chinese and English treebank annotations were performed independently. The parallel texts were then word aligned. The material in this release corresponds to portions of the treebanked data in OntoNotes 3.0 (LDC2009T24) and OntoNotes 4.0 (LDC2011T03). This release consists of English source broadcast programming (CNN, NBC/MSNBC) and web data collected by LDC in 2005 and 2006. GALE English-Chinese Parallel Aligned Treebank – Training is distributed via web download.
2017 Subscription Members will automatically receive copies of this corpus. 2017 Standard Members may request a copy as part of their 16 free membership corpora. Non-members may license this data for US $1750.
Membership Office University of Pennsylvania T: +1-215-573-1275 E: ldc@ldc.upenn.edu M: 3600 Market St. Suite 810 Philadelphia, PA 19104
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