[Corpora-List] New from LDC

Linguistic Data Consortium ldc at ldc.upenn.edu
Tue Feb 26 22:55:28 CET 2013


*Spring 2013 LDC Data Scholarship Recipients <#scholar>***

/New publications:/

*GALE Phase 2 Arabic Broadcast Conversation Speech Part 1 <#gale1>***

**

*GALE Phase 2 Arabic Broadcast Conversation Transcripts - Part 1 <#gale2>***

**

***NIST 2012 Open Machine Translation (OpenMT) Evaluation <#mt>*

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*Spring 2013 LDC Data Scholarship Recipients*

LDC is pleased to announce the student recipients of the Spring 2013 LDC Data Scholarship program! This program provides university students with access to LDC data at no-cost. Students were asked to complete an application which consisted of a proposal describing their intended use of the data, as well as a letter of support from their thesis adviser. We received many solid applications and have chosen three proposals to support. The following students will receive no-cost copies of LDC data:

Salima Harrat - Ecole Supérieure d'informatique (ESI) (Algeria).

Salima has been awarded a copy of /Arabic Treebank: Part 3/ for her

work in diacritization restoration.

Maulik C. Madhavi - Dhirubhai Ambani Institute of Information and

Communication Technology (DA-IICT), Gandhinagar (India). Maulik has

been awarded a copy of /Switchboard Cellular Part 1 Transcribed

Audio and Transcripts/ and /1997 HUB4 English Evaluation Speech and

Transcripts/ for his work in spoken term detection.

Shereen M. Oraby - Arab Academy for Science, Technology, and

Maritime Transport (Egypt). Shereen has been awarded a copy of

/Arabic Treebank: Part 1/ for her work in subjectivity and sentiment

analysis.

Please join us in congratulating our student recipients! The next LDC Data Scholarship program is scheduled for the Fall 2013 semester.

*New publications*

(1) GALE Phase 2 Arabic Broadcast Conversation Speech Part 1 <http://www.ldc.upenn.edu/Catalog/catalogEntry.jsp?catalogId=LDC2013S02> was developed by LDC and is comprised of approximately 123 hours of Arabic broadcast conversation speech collected in 2006 and 2007 by LDC as part of the DARPA GALE (Global Autonomous Language Exploitation) Program. Broadcast audio for the DARPA GALE program was collected at LDC's Philadelphia, PA USA facilities and at three remote collection sites. The combined local and outsourced broadcast collection supported GALE at a rate of approximately 300 hours per week of programming from more than 50 broadcast sources for a total of over 30,000 hours of collected broadcast audio over the life of the program.

LDC's local broadcast collection system is highly automated, easily extensible and robust and capable of collecting, processing and evaluating hundreds of hours of content from several dozen sources per day. The broadcast material is served to the system by a set of free-to-air (FTA) satellite receivers, commercial direct satellite systems (DSS) such as DirecTV, direct broadcast satellite (DBS) receivers, and cable television (CATV) feeds. The mapping between receivers and recorders is dynamic and modular; all signal routing is performed under computer control, using a 256x64 A/V matrix switch. Programs are recorded in a high bandwidth A/V format and are then processed to extract audio, to generate keyframes and compressed audio/video, to produce time-synchronized closed captions (in the case of North American English) and to generate automatic speech recognition (ASR) output.

The broadcast conversation recordings in this release feature interviews, call-in programs and round table discussions focusing principally on current events from several sources. This release contains 143 audio files presented in .wav, 16000 Hz single-channel 16-bit PCM. Each file was audited by a native Arabic speaker following Audit Procedure Specification Version 2.0 which is included in this release. The broadcast auditing process served three principal goals: as a check on the operation of LDCs broadcast collection system equipment by identifying failed, incomplete or faulty recordings; as an indicator of broadcast schedule changes by identifying instances when the incorrect program was recorded; and as a guide for data selection by retaining information about a program's genre, data type and topic.

*

(2) GALE Phase 2 Arabic Broadcast Conversation Transcripts - Part 1 <http://www.ldc.upenn.edu/Catalog/catalogEntry.jsp?catalogId=LDC2013T04> was developed by LDC and contains transcriptions of approximately 123 hours of Arabic broadcast conversation speech collected in 2006 and 2007 by LDC, MediaNet, Tunis, Tunisia and MTC, Rabat, Morocco during Phase 2 of the DARPA GALE (Global Autonomous Language Exploitation) program. The source broadcast conversation recordings feature interviews, call-in programs and round table discussions focusing principally on current events from several sources.

The transcript files are in plain-text, tab-delimited format (TDF) with UTF-8 encoding, and the transcribed data totals 752,747 tokens. The transcripts were created with the LDC-developed transcription tool, XTrans <http://www.ldc.upenn.edu/tools/XTrans/downloads/>, a multi-platform, multilingual, multi-channel transcription tool that supports manual transcription and annotation of audio recordings.

The files in this corpus were transcribed by LDC staff and/or by transcription vendors under contract to LDC. Transcribers followed LDCs quick transcription guidelines (QTR) and quick rich transcription specification (QRTR) both of which are included in the documentation with this release. QTR transcription consists of quick (near-)verbatim, time-aligned transcripts plus speaker identification with minimal additional mark-up. It does not include sentence unit annotation. QRTR annotation adds structural information such as topic boundaries and manual sentence unit annotation to the core components of a quick transcript. Files with QTR as part of the filename were developed using QTR transcription. Files with QRTR in the filename indicate QRTR transcription.

*

(3) NIST 2012 Open Machine Translation (OpenMT) Evaluation <http://www.ldc.upenn.edu/Catalog/catalogEntry.jsp?catalogId=LDC2013T03> was developed by NIST Multimodal Information Group <http://nist.gov/itl/iad/mig/>. This release contains source data, reference translations and scoring software used in the NIST 2012 OpenMT evaluation, specifically, for the Chinese-to-English language pair track. The package was compiled and scoring software was developed at NIST, making use of Chinese newswire and web data and reference translations collected and developed by LDC. The objective of the OpenMT evaluation series is to support research in, and help advance the state of the art of, machine translation (MT) technologies -- technologies that translate text between human languages. Input may include all forms of text. The goal is for the output to be an adequate and fluent translation of the original.

The 2012 task was to evaluate five language pairs: Arabic-to-English, Chinese-to-English, Dari-to-English, Farsi-to-English and Korean-to-English. This release consists of the material used in the Chinese-to-English language pair track. For more general information about the NIST OpenMT evaluations, please refer to the NIST OpenMT website <http://www.nist.gov/itl/iad/mig/openmt.cfm>.

This evaluation kit includes a single Perl script (mteval-v13a.pl) that may be used to produce a translation quality score for one (or more) MT systems. The script works by comparing the system output translation with a set of (expert) reference translations of the same source text. Comparison is based on finding sequences of words in the reference translations that match word sequences in the system output translation.

This release contains 222 documents with corresponding source and reference files, the latter of which contains four independent human reference translations of the source data. The source data is comprised of Chinese newswire and web data collected by LDC in 2011. A portion of the web data concerned the topic of food and was treated as a restricted domain. The table below displays statistics by source, genre, documents, segments and source tokens.

*Source***

*Genre***

*Documents***

*Segments***

*Source Tokens***

Chinese General

Newswire

45

400

18184

Chinese General

Web Data

28

420

15181

Chinese Restricted Domain

Web Data

149

2184

48422

The token counts for Chinese data are "character" counts, which were obtained by counting tokens matching the UNICODE-based regular expression "/w". The Python "re" module was used to obtain those counts.

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-- --

Ilya Ahtaridis Membership Coordinator -------------------------------------------------------------------- Linguistic Data Consortium Phone: 1 (215) 573-1275 University of Pennsylvania Fax: 1 (215) 573-2175 3600 Market St., Suite 810ldc at ldc.upenn.edu Philadelphia, PA 19104 USAhttp://www.ldc.upenn.edu

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