- *Fall 2010 LDC Data Scholarship Program <#scholar>* -
*- **New Providing Guideline*s <8#provide>* -*
LDC2010S05 *- Asian Elephant Vocalizations <#elephant>** - *
LDC2010T14 *- **NIST 2005 Open Machine Translation (OpenMT) Evaluation <#openmt>** -*
LDC2010V02 *- TRECVID 2006 Keyframes <#trecvid>** - * * * ------------------------------------------------------------------------ * *
*Fall 2010 LDC Data Scholarship Program*
Applications are now being accepted through September 15, 2010 for the Fall 2010 LDC Data Scholarship program! The LDC Data Scholarship program provides university students with access to LDC data at no-cost. Data scholarships are offered twice a year to correspond to the Fall and Spring semesters, beginning with the Fall 2010 semester (September - December 2010). Several students can be awarded scholarships during each program cycle. This program is open to students pursuing both undergraduate and graduate studies in an accredited college or university. LDC Data Scholarships are not restricted to any particular field of study; however, students must demonstrate a well-developed research agenda and a bona fide inability to pay.
The application consists of two parts:
(1) /*Data Use Proposal*/. Applicants must submit a proposal describing their intended use of the data. The proposal must contain the applicant's name, university, and field of study. The proposal should state which data the student plans to use and contain a description of their research project. Students are advised to consult the LDC Corpus Catalog <http://www.ldc.upenn.edu/Catalog/index.jsp> for a complete list of data distributed by LDC. Due to certain restrictions, a handful of LDC corpora are restricted to members of the Consortium.
(2) /*Letter of Support*/. Applicants must submit one letter of support from their thesis advisor or department chair. The letter must verify the student's need for data and confirm that the department or university lacks the funding to pay the full Non-member Fee for the data.
For further information on application materials and program rules, please visit the LDC Data Scholarship <http://www.ldc.upenn.edu/About/scholarships.html> page.
Students can email their applications to the LDC Data Scholarship program <mailto:datascholarships at ldc.upenn.edu>. Decisions will be sent by email from the same address.
The deadline for the Fall 2010 program cycle is September 15, 2010.
Track the LDC Data Scholarship program at WikiCFP <http://www.wikicfp.com/>!
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*New Providing Guidelines*
LDC is pleased to announce that our Providing <http://www.ldc.upenn.edu/Providing/> page has been recently updated and enhanced to reflect detailed guidelines for submitting corpora and other resources for publication by LDC. The new Providing page describes the entire process of sharing data through LDC from the initial publication inquiry to delivery of the data for publication. LDC's preferred submission formats for video, audio, and text data and directory structure, and best practices for file naming conventions are covered in depth. The page also includes information on providing adequate metadata and documentation of your data set.
Researchers interested in publishing data through LDC are invited to use the Publication Inquiry Form <http://www.ldc.upenn.edu/Providing/subform.html>. The inquiry form will prompt you for basic information about your data including title, author, language, details on corpus size and format, as well as a description. Once your inquiry has been received, our External Relations staff can assist you through each step of the publication process.
Why share your data through LDC? Resources distributed by LDC reach a global audience. All published resources appear in LDC's online Catalog <http://www.ldc.upenn.edu/Catalog>, which is accessed daily by users worldwide. LDC's monthly newsletter keeps the community abreast of all new publications, and its reach ensures the attention of interested researchers. LDC members receive copies of the corpora as part of their membership benefits. LDC's Membership structure therefore guarantees your data greater exposure to major organizations working in human language technologies and related fields.
The LDC Corpus Catalog contains a variety of resources in many languages and formats ranging from written to spoken and video. Speech and video data may derive from broadcast collections, interviews, and recordings of telephone conversations. Text data comes from a variety of sources including newswire, document archives and anthologies as well as the World Wide Web. LDC also publishes dictionaries and lexicons in a variety of languages.
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(1) Asian Elephant Vocalizations <http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010S05> consists of 57.5 hours of audio recordings of vocalizations by Asian Elephants (/Elephas maximus/) in the Uda Walawe National Park, Sri Lanka, of which 31.25 hours have been annotated. The collection and annotation of the recordings was conducted and overseen by Shermin de Silva, of the University of Pennsylvania Department of Biology; voice recording field notes are of Shermin de Silva and Ashoka Ranjeewa. The recordings primarily feature adult female and juvenile elephants. Existing knowledge of acoustic communication in elephants is based primarily on African species (/Loxodonta africana/ and /Loxodonta cyclotis/). There has been comparatively less study of communication in Asian elephants.
This corpus is intended to enable researchers in acoustic communication to evaluate acoustic features and repertoire diversity of the recorded population. Of particular interest is whether there may be regional dialects that differ among Asian elephant populations in the wild and in captivity. A second interest is in whether structural commonalities exist between this and other species that shed light on underlying social and ecological factors shaping communication systems.
Data were collected from May, 2006 to December, 2007. Observations were performed by vehicle during park hours from 0600 to 1830 h. Most recordings of vocalizations were made using an Earthworks QTC50 microphone shock-mounted inside a Rycote Zeppelin windshield, via a Fostex FR-2 field recorder (24-bit sample size, sampling rate 48 kHz). Recordings were initiated at the start of a call with a 10-s pre-record buffer so that the entire call was captured and loss of rare vocalizations minimized. This was made possible with the 'pre-record' feature of the Fostex, which records continuously, but only saves the file with a 10-second lead once the 'record' button is depressed.
Certain audio files were manually annotated, to the extent possible, with call type, caller id, and miscellaneous notes. For call type annotation, there are three main categories of vocalizations: those that show clear fundamental frequencies (periodic), those that do not (a-periodic), and those that show periodic and a-periodic regions as at least two distinct segments. Calls were identified as belonging to one of 14 categories. Annotations were made using the Praat TextGrid Editor <http://www.fon.hum.uva.nl/praat/manual/TextGridEditor.html>, which allows spectral analysis and annotation of audio files with overlapping events. Annotations were based on written and audio-recorded field notes, and in some cases video recordings. Miscellaneous notes are free-form, and include such information as distance from source, caller identity certainty, and accompanying behavior.
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(2) NIST 2005 Open Machine Translation (OpenMT) Evaluation <http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T14> is a package containing source data, reference translations, and scoring software used in the NIST 2005 OpenMT evaluation. It is designed to help evaluate the effectiveness of machine translation systems. The package was compiled and scoring software was developed by researchers at NIST, making use of newswire source data and reference translations collected and developed by LDC.
The objective of the NIST 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 2004 task was to evaluate translation from Chinese to English and from Arabic to English. Additional information about these evaluations may be found at the NIST Open Machine Translation (OpenMT) Evaluation web site <http://www.itl.nist.gov/iad/mig/tests/mt/>.
This evaluation kit includes a single perl script (mteval-v11a.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 corpus consists of 100 Arabic newswire documents, 100 Chinese newswire documents, and a corresponding set of four separate human expert reference translations. Source text for both languages was collected from Agence France-Presse and Xinhua News Agency in December 2004 and January 2005.
For each language, the test set consists of two files: a source and a reference file. Each reference file contains four independent translations of the data set. The evaluation year, source language, test set, version of the data, and source vs. reference file are reflected in the file name.
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(3) TRECVID 2006 Keyframes <http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010V02> was developed as a collaborative effort between researchers at LDC, NIST <http://www.nist.gov/>, LIMSI-CNRS <http://www.limsi.fr/>, and Dublin City University <http://www.dcu.ie/> TREC Video Retrieval Evaluation (TRECVID) is sponsored by the National Institute of Standards and Technology (NIST) to promote progress in content-based retrieval from digital video via open, metrics-based evaluation. The keyframes in this release were extracted for use in the NIST TRECVID 2006 Evaluation.
TRECVID is a laboratory-style evaluation that attempts to model real world situations or significant component tasks involved in such situations. In 2006 TRECVID completed a 2-year cycle on English, Arabic, and Chinese news video. There weree three system tasks and associated tests:
* shot boundary determination
* high-level feature extraction
* search (interactive, manually-assisted, and/or fully automatic)
For a detailed description of the TRECVID Evaluation Tasks, please refer to the NIST TRECVID 2006 Evaluation Description. <http://www-nlpir.nist.gov/projects/tv2006/>
The video stills that compose this corpus are drawn from approximately 158.6 hours of English, Arabic, and Chinese language video data collected by LDC from NBC, CNN, MSNBC, New Tang Dynasty TV, Phoenix TV, Lebanese Broadcasting Corp., and China Central TV.
Shots are fundamental units of video, useful for higher-level processing. To create the master list of shots, the video was segmented. The results of this pass are called subshots. Because the master shot reference is designed for use in manual assessment, a second pass over the segmentation was made to create the master shots of at least 2 seconds in length. These master shots are the ones used in submitting results for the feature and search tasks in the evaluation. In the second pass, starting at the beginning of each file, the subshots were aggregated, if necessary, until the current shot was at least 2 seconds in duration, at which point the aggregation began anew with the next subshot.
The keyframes were selected by going to the middle frame of the shot boundary, then parsing left and right of that frame to locate the nearest I-Frame. This then became the keyframe and was extracted. Keyframes have been provided at both the subshot (NRKF) and master shot (RKF) levels.
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Ilya Ahtaridis Membership Coordinator -------------------------------------------------------------------- Linguistic Data Consortium Phone: (215) 573-1275 University of Pennsylvania Fax: (215) 573-2175 3600 Market St., Suite 810 ldc at ldc.upenn.edu Philadelphia, PA 19104 USA http://www.ldc.upenn.edu
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