<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
</head>
<body bgcolor="#ffffff" text="#000000">
<p class="MsoNormal" style="text-align: center;" align="center"><i>In
this newsletter:</i><b><br>
</b></p>
<p class="MsoNormal" style="text-align: center;" align="center"><b>- <a
href="#scholar">Fall
2010 LDC Data
Scholarship Winners!</a></b><b> -</b></p>
<p class="MsoNormal" style="text-align: center;" align="center"><b>- </b><b>
</b><b><a href="#jobs">Position
Openings at LDC</a></b><b> -</b></p>
<p class="MsoNormal" style="text-align: center;" align="center"><i><br>
New
Publications:</i><br>
</p>
<p class="MsoNormal" style="text-align: center;" align="center">LDC2010T18<br>
</p>
<p class="MsoNormal" style="text-align: center;" align="center"><b>- <a
href="#ace">ACE
Time Normalization (<st1:stockticker>TERN</st1:stockticker>)
2004 English Evaluation Data V1.0</a></b><b> -<br>
</b></p>
<p class="MsoNormal" style="text-align: center;" align="center">LDC2010T19<br>
<b>- <a href="#korean">Korean
Newswire Second Edition</a></b><b> -<br>
</b></p>
<p class="MsoNormal" style="text-align: center;" align="center">LDC2010T17<br>
<b><st1:stockticker>- </st1:stockticker><a href="#openmt"><st1:stockticker>NIS</st1:stockticker>T
2006 Open Machine Translation
(OpenMT)
Evaluation</a></b><b><st1:stockticker></st1:stockticker> -</b></p>
<hr size="2" width="100%">
<p class="MsoNormal" style="text-align: center;" align="center"><b><br>
</b></p>
<p class="MsoNormal" align="center"><a name="scholar"></a><b>Fall 2010
LDC Data
Scholarship Winners!</b><b><br>
</b></p>
<p class="MsoNormal">LDC is pleased to announce the winners in our
first-ever 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. Students are
asked
to complete an application which consists of a data use proposal and
letter of
support from their academic adviser. <br>
<br>
LDC received many strong applications from both undergraduate and
graduate
students attending universities across the globe. The decision process
was difficult, and after much deliberation, we have selected eight
winners!
These students will receive no-cost copies of LDC data valued at over
US$10,000:<br>
</p>
<blockquote>
<p class="MsoNormal">Aby Abraham - Ohio University (USA), graduate
student, Electrical
Engineering. Aby has been awarded a copy of <i>2003 NIST Speaker
Recognition Evaluation (LDC2010S03)</i> for his work in using long term
memory
cells for continuous speech recognition.<br>
<o:p></o:p></p>
<p class="MsoNormal">Ripandy Adha - Bandung Institute of Technology (<st1:country-region><st1:place>Indonesia</st1:place></st1:country-region>),
undergraduate student, Computer Science - Ripandy has been awarded a
copy of <i>American
English Spoken Lexicon (LDC99L23)</i> to assist in the development of a
voice
command internet browser.<br>
<br>
Basawaraj - Ohio University (USA), PhD candidate, Electrical
Engineering and
Computer Science. Basawaraj has been awarded a copy of <i>NIST 2002
Open Machine Translation (OpenMT) Evaluation (LDC2010T10)</i> to assist
in fine
tuning his machine translation system and to provide a benchmark
dataset.<br>
<br>
Zachary Brooks - University of <st1:state><st1:place>Arizona</st1:place></st1:state>
(<st1:country-region><st1:place>USA</st1:place></st1:country-region>),
PhD
Candidate, Second Language Acquisition and Teaching. Zachary and his
research group have been awarded a copy of <i>ECI Multilingual Text
(LDC94T5)</i>
for research in eye movement tracking by native and non-natives readers.<br>
<br>
Marco Carmosino - Hampshire College (USA), undergraduate student,
Computer
Science. Marco has been awarded a copy of <i>English Gigaword Fourth
Edition (LDC2009T13)</i> for his work in narrative chain extraction.<br>
<br>
Xiaohui Huang - Harbin Institute of Technology (<st1:country-region><st1:place>China</st1:place></st1:country-region>),
<st1:place><st1:placename>Shenzhen</st1:placename> <st1:placename>Graduate</st1:placename>
<st1:placetype>School</st1:placetype></st1:place>. Xiaohui has been
awarded a copy of <i>TDT5 Topics and Annotations (LDC2006T19)</i> for
his
work in topic detection and tracking for large-scale web data.<o:p></o:p></p>
<p class="MsoNormal">Yuhuan Zhou - PLA University of Science and
Technology (<st1:country-region><st1:place>China</st1:place></st1:country-region>),
postgraduate student, <st1:place><st1:placetype>Institute</st1:placetype>
of <st1:placename>Communications Engineering</st1:placename></st1:place>.
Yuhuan has been awarded a copy
of <i>2002 NIST Speaker Recognition Evaluation (LDC2004S04)</i> to
assist in
the development of a speaker recognition system which fuses support
vector data
description (SVDD) and Gaussian mixture model (GMM). <o:p></o:p></p>
<p class="MsoNormal">Speaker Recognition Group (GEDA) with members
Matias
Fineschi, Gonzalo Lavigna, Jorge Prendes, and Pablo Vacatello - Buenos
Aires Institute of Technology (Argentina), Department of Electrical
Engineering. GEDA has been awarded a copy of <i>2004 NIST Speaker
Recognition Evaluation (LDC2006S44)</i> to assist in the development of
a
flexible platform on speaker verification capable of implementing
different
feature extraction, normalizations, stochastical models and outputs.<o:p></o:p></p>
</blockquote>
<p class="MsoNormal" style="margin-bottom: 12pt;">Please join us in
congratulating our student winners! The next LDC Data Scholarship
program is scheduled for the Spring 2011 semester. Stay tuned for
further
announcements.</p>
<p class="MsoNormal" style="margin-bottom: 12pt;">[<a href="#top">
top </a>]
<!--[if !supportLineBreakNewLine]--><br style="">
<!--[endif]--><o:p></o:p></p>
<p style="text-align: center;" align="center"><o:p></o:p></p>
<p style="text-align: center;" align="center"><o:p> </o:p></p>
<p style="margin-bottom: 12pt; text-align: center;" align="center"><b> </b><a
name="jobs"></a><b>Position Openings at LDC<br>
</b></p>
<div align="left">Linguistic Data Consortium at the University of
Pennsylvania has a number of immediate openings for full-time positions
to support our corpus development projects:<br>
<br>
<blockquote>
<ul>
<li>PROGRAMMER ANALYST - (#100528459 and #100929195)</li>
</ul>
Support linguistic data collection and annotation projects by providing
software development, system integration, technical and research
support, annotation tool development and/or data collection system
management. <br>
<br>
<ul>
<li>SENIOR PROJECT MANAGER (#100728923 and #100728924)</li>
</ul>
Provide complete oversight for multiple, concurrent corpus creation
projects, including collection, annotation and distribution of speech,
text and/or video data in a variety of languages. Create project
roadmaps and direct teams of programmers, linguists and managers to
execute deliverables; represent corpus creation efforts to external
researchers and sponsors.<br>
<br>
<ul>
<li>LEAD ANNOTATOR (#100728920)</li>
</ul>
Perform linguistic annotation on English text, speech and video data;
recruit, train and supervise teams of annotators for multiple tasks and
languages; define, test and document procedural approaches to
linguistic annotation;perform quality control on annotated data. <br>
<p style="margin-bottom: 12pt; text-align: center;" align="center"><o:p></o:p></p>
</blockquote>
</div>
<p style="margin-bottom: 12pt;">For further information on the duties
and qualifications for these positions,
or to apply online please visit <a href="https://jobs.hr.upenn.edu/">https://jobs.hr.upenn.edu/</a>;
search postings for the reference numbers indicated above.<br>
<br>
Penn offers an excellent benefits package including medical/dental,
retirement
plans, tuition assistance and a minimum of three weeks paid vacation
per year.
The <st1:place><st1:placetype>University</st1:placetype> of <st1:placename>Pennsylvania</st1:placename></st1:place>
is an affirmative action/equal opportunity employer. All positions
contingent upon grant funding.<br>
.<br>
For more information about LDC and the programs we support, visit <a
href="http://www.ldc.upenn.edu/">http://www.ldc.upenn.edu/</a>.</p>
<p style="margin-bottom: 12pt;">[<a href="#top">
top </a>]
<br>
<o:p></o:p></p>
<p style="margin-bottom: 12pt; text-align: center;" align="center"><b><br>
New
Publications</b><o:p></o:p></p>
<p><a name="ace"></a>(1) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T18">ACE
Time Normalization (TERN) 2004 English Evaluation Data V1.0</a> was
developed
by researchers at <a href="http://www.mitre.org/">The MITRE Corporation</a>.
It
contains the English evaluation data prepared for the <a
href="http://fofoca.mitre.org/tern.html">2004 Time Expression
Recognition and
Normalization (TERN) Evaluation</a>, sponsored by the <a
href="http://www.itl.nist.gov/iad/mig/tests/ace/">Automatic Content
Extraction
(ACE)</a> program, specifically, English broadcast news and newswire
data
collected by LDC. The training data for this evaluation can be found in
<a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2005T07">ACE
Time Normalization (TERN) 2004 English Training Data v 1.0 LDC2005T07</a>.
<br>
<br>
The purpose of the TERN evaluation is to advance the state of the art
in the
automatic recognition and normalization of natural language temporal
expressions. In most language contexts such expressions are indexical.
For
example, with "Monday," "last week," or "three months
starting October 1," one must know the narrative reference time in
order
to pinpoint the time interval being conveyed by the expression. In
addition,
for data exchange purposes, it is essential that the identified
interval be
rendered according to an established standard, i.e., normalized.
Accurate
identification and normalization of temporal expressions are in turn
essential
for the temporal reasoning being demanded by advanced NLP applications
such as
question answering, information extraction and summarization. <o:p></o:p></p>
<p>The data in this release is English broadcast transcripts and
newswire
material from <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2005T16">TDT4
Multilingual Text and Annotations LDC2005T16</a>. The annotation
specifications
for this corpus were developed under DARPA's <a
href="http://projects.ldc.upenn.edu/TIDES/">Translingual Information
Detection
Extraction and Summarization (TIDES)</a> program, with support from
ACE. All
files have been doubly-annotated by two separate annotators and then
reconciled,
using the TIDES 2003 Standard for the Annotation of Temporal
Expressions.
The data directory contains the corpus which consists of 192 files (54K
words).<o:p></o:p></p>
<p class="MsoNormal"><br>
</p>
<p class="MsoNormal">[<a href="#top">
top </a>]
</p>
<div align="center">*<br>
</div>
<p class="MsoNormal"><a name="korean"></a>(2) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T19">Korean
Newswire Second Edition</a> is an archive of Korean newswire text that
has been
acquired over several years (1994-2009) at LDC from the Korean Press
Agency.
This release includes all of the content of <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2000T45">Korean
Newswire (LDC2000T45)</a> (June 1994-March 2000) as well as
newly-collected
data. The second edition contains all data collected by LDC from April
2000 through December 2009. <o:p></o:p></p>
<p>All material, including that from the first release, has been
converted to
UTF-8 (except for more recent data already in UTF-8 format) and
processed in
LDC's gigaword format. The gigaword format classifies newswire content
into
three types: story, multi and other where "story" refers to an
article containing information pertaining to a particular event on a
day;
"multi" refers to an article that contains more than one story
relating to different topics; and "other" refers to articles containing
lists, tables or numerical data, such as sports scores. <o:p></o:p></p>
<p>A word break error in the original release and in data collected
from
January 2002 through February 2005 has been corrected in the second
edition
with the result that all Korean text should display correctly. The
error
involved a line break in the middle of a word with the result that an
affected
word appeared in segments in two lines. This problem was <span style=""> </span>resolved
using word histograms and a few <br>
</p>
<p class="MsoNormal">[<a href="#top">
top </a>]
</p>
<div align="center">*<br>
</div>
<p class="MsoNormal"><o:p></o:p></p>
<p><a name="openmt"></a>(3) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T17">NIST
2006 Open Machine Translation (OpenMT) Evaluation</a> is a package
containing
source data, reference translations and scoring software used in the
NIST 2006
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 broadcast, newswire and
web
newsgroup source data and reference translations collected and
developed by
LDC. <o:p></o:p></p>
<p>The objective of the NIST Open Machine Translation (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
OpenMT evaluations are intended to be of interest to all researchers
working on
the general problem of automatic translation between human languages.
To this
end, they are designed to be simple, to focus on core technology issues
and to
be fully supported. The 2006 task was to evaluate translation from
Arabic to
English and from Chinese to English. Additional information about
these
evaluations may be found at the <a
href="http://www.itl.nist.gov/iad/mig/tests/mt/">NIST Open Machine
Translation
(OpenMT) Evaluation web site</a>. <o:p></o:p></p>
<p>This evaluation kit includes a single Perl script (mteval-v11b.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. <o:p></o:p></p>
<p>The included scoring script was released with the original
evaluation, intended
for use with SGML-formatted data files, and is provided to ensure
compatibility
of user scoring results with results from the original evaluation. An
updated
scoring software package (mteval-v13a-20091001.tar.gz), with XML
support,
additional options and bug fixes, documentation, and example
translations, may
be downloaded from the <a href="http://www.itl.nist.gov/iad/mig/tools/">NIST
Multimodal Information Group Tools</a> website. <o:p></o:p></p>
This release contains of 357 documents with
corresponding
sets of four separate human expert reference translations. The source
data is
comprised of Arabic and Chinese newswire documents, human
transcriptions of
broadcast news and broadcast conversation programs and web newsgroup
documents
collected by LDC in 2006. The newswire and broadcast material are from
Agence
France-Presse (Arabic, Chinese), Xinhua News Agency (Arabic, Chinese),
Lebanese
Broadcasting Corp. (Arabic), Dubai TV (Arabic), China Central TV
(Chinese) and
New Tang Dynasty Television (Chinese). The web text was collected from
Google
and Yahoo newsgroups. <br>
<br>
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.<br>
<br>
[<a href="#top">
top </a>]
<hr size="2" width="100%">
<div align="center">
<pre class="moz-signature" cols="72">Ilya Ahtaridis
Membership Coordinator
--------------------------------------------------------------------
Linguistic Data Consortium Phone: 1 (215) 573-1275
University of Pennsylvania Fax: 1 (215) 573-2175
3600 Market St., Suite 810 <a
class="moz-txt-link-abbreviated" href="mailto:ldc@ldc.upenn.edu">ldc@ldc.upenn.edu</a>
Philadelphia, PA 19104 USA <a
class="moz-txt-link-freetext" href="http://www.ldc.upenn.edu">http://www.ldc.upenn.edu</a></pre>
</div>
<pre class="moz-signature" cols="72">
</pre>
</body>
</html>