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<p class="MsoNormal" style="margin-bottom: 12pt; text-align: center;"
align="center"><i>In
this newsletter:</i><b><br>
<br>
- <a href="#data">Coming
Soon: LDC Data Scholarship Program!</a> -</b><br>
<br>
<i>New publications:<br>
</i><br>
LDC2010S03<br>
<b>- <a href="#2003sre">2003
NIST Speaker Recognition Evaluation</a> -</b><br>
<br>
LDC2010T09<br>
<b>- <a href="#ace2005">ACE
2005 Mandarin SpatialML Annotations</a> -</b><br>
<br>
LDC2010T10<br>
<b>- <a href="#2002mt">NIST
2002 Open Machine Translation (OpenMT)
Evaluation</a> -</b><b></b><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<div class="MsoNormal" style="text-align: center;" align="center">
<hr align="center" size="2" width="100%"></div>
<p class="MsoNormal" style="text-align: center;" align="center"><b><o:p> </o:p></b></p>
<p class="MsoNormal" style="text-align: center;" align="center"><b><a
name="data"></a>Coming
Soon: LDC Data Scholarship Program!</b><o:p></o:p></p>
<p>We are pleased to announce that the LDC Data
Scholarship program is in the
works! This program will provide university students with access to LDC
data at
no-cost. Each year LDC distributes thousands of dollars worth of data
at no- or
reduced-cost to students who demonstrate a need for data, yet cannot
secure
funding. LDC will formalize this practice through the newly created
LDC
Data Scholarship program. <o:p></o:p></p>
<p>Data scholarships will be offered each semester beginning with the
fall 2010
semester (September - December 2010). Students will need to complete an
application, which will include a data use proposal and letter of
support from
their faculty adviser. We anticipate that the selection process will
be
highly competitive.<o:p></o:p></p>
<p>Stay tuned for further announcements in our newsletter and on our
home page!<br>
</p>
<p><br>
[<a href="#top">
top </a>]<br>
<o:p></o:p></p>
<p class="MsoNormal" style="text-align: center;" align="center"><b>New
Publications<o:p></o:p></b></p>
<p class="MsoNormal" style="text-align: center;" align="center"><b><o:p> </o:p></b></p>
<p><a name="2003sre"></a>(1) <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010S03">2003
NIST Speaker Recognition Evaluation</a> was developed by researchers at
NIST
(National Institute of Standards and Technology). It consists of just
over 120
hours of English conversational telephone speech used as training data
and test
data in the 2003 Speaker Recognition Evaluation (<st1:stockticker>SRE</st1:stockticker>),
along with evaluation metadata and test set answer keys.<o:p></o:p></p>
<p>2003 NIST Speaker Recognition Evaluation is part of an ongoing
series of
yearly evaluations conducted by NIST. These evaluations provide an
important
contribution to the direction of research efforts and the calibration
of
technical capabilities. They are intended to be of interest to all
researchers
working on the general problem of text independent speaker recognition.
To this
end the evaluation was designed to be simple, to focus on core
technology
issues, to be fully supported, and to be accessible to those wishing to
participate. <o:p></o:p></p>
<p class="MsoNormal" style="">This
speaker recognition evaluation focused on the task of 1-speaker and
2-speaker
detection, in the context of conversational telephone speech.<span
style=""> </span>The original evaluation consisted of three
parts: 1-speaker detection "limited data", 2-speaker detection
"limited data", and 1-speaker detection "extended data".
This corpus contains training and test data and supporting metadata
(including
answer keys) for only the 1-speaker "limited data" and 2-speaker
"limited data" components of the original evaluation. The 1-speaker
"extended data" component of the original evaluation (not included in
this corpus) provided metadata only, to be used in conjunction with
data from <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC99S79">Switchboard-2
Phase II (LDC99S79)</a> and <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2002S06">Switchboard-2
Phase III Audio (LDC2002S06)</a>. The metadata (resources and answer
keys) for
the 1-speaker "extended data" component of the original 2003 SRE
evaluation are available from the NIST Speech Group website for the <a
href="http://www.itl.nist.gov/iad/mig/tests/sre/2003/index.html">2003
Speaker
Recognition Evaluation</a>. <o:p></o:p></p>
<p>The data in this corpus is a 120-hour subset of data first made
available to
the public as <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2004S07">Switchboard
Cellular Part 2 Audio (LDC2004S07)</a>, reorganized specifically for
use in the
2003 <st1:stockticker>NIS</st1:stockticker>T SRE.<o:p></o:p></p>
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<div align="center">*<br>
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<p class="MsoNormal"><o:p></o:p></p>
<p><a name="ace2005"></a>(2)<span style=""> </span><a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T09">ACE
2005 Mandarin SpatialML Annotations</a> was developed by researchers at
<a href="http://www.mitre.org/">The MITRE Corporation</a> (MITRE). ACE
2005
Mandarin SpatialML Annotations applies SpatialML tags to a subset of
the source
Mandarin training data in ACE 2005 Multilingual Training Corpus
(LDC2006T06). <o:p></o:p></p>
<p>SpatialML is a mark-up language for representing spatial expressions
in
natural language documents. SpatialML focuses is on geography and
culturally-relevant landmarks, rather than biology, cosmology, geology,
or
other regions of the spatial language domain. The goal is to allow for
better
integration of text collections with resources such as databases that
provide
spatial information about a domain, including gazetteers, physical
feature
databases and mapping services. <o:p></o:p></p>
<p>The SpatialML annotation scheme is intended to emulate earlier
progress on
time expressions such as <a href="http://fofoca.mitre.org/">TIMEX2</a>,
<a href="http://www.timeml.org/site/index.html">TimeML</a>, and the <a
href="http://www.itl.nist.gov/iad/mig/tests/ace/2005/doc/ace05eval_official_results_20060110.html">2005
ACE guidelines</a>. The main SpatialML tag is the PLACE tag which
encodes
information about location. The central goal of SpatialML is to map
location
information in text to data from gazetteers and other databases to the
extent
possible by defining attributes in the PLACE tag. Therefore, semantic
attributes such as country abbreviations, country subdivision and
dependent
area abbreviations (e.g., US states), and geo-coordinates are used to
help
establish such a mapping. The SpatialML guidelines are compatible with
existing
guidelines for spatial annotation and existing corpora within the ACE
research
program. <o:p></o:p></p>
<p>This corpus consists of a 298-document subset of broadcast material
from the
ACE 2005 Multilingual Training Corpus (LDC2006T06) that has been tagged
by a
native Mandarin speaker according to version 2.3 of the SpatialML
annotation
guidelines, which are included in the documentation for this release. <o:p></o:p></p>
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<p><a name="2002mt"></a>(3)<span style=""> </span><a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2010T10">NIST
2002 Open Machine Translation (OpenMT) Evaluation</a> is a package
containing
source data, reference translations, and scoring software used in the
NIST 2002
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. <o:p></o:p></p>
<p>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. 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 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 Chinese-language source text included in this corpus is a
reorganization
of data that was initially released to the public as <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2003T17">Multiple-Translation
Chinese (MTC) Part 2 (LDC2003T17)</a>. The Chinese-language reference
translations are a reorganized subset of data from the same MTC corpus.
The
Arabic-language data (source text and reference translations) is a
reorganized
subset of data that was initially released to the public as <a
href="http://www.ldc.upenn.edu/Catalog/CatalogEntry.jsp?catalogId=LDC2003T18">Multiple-Translation
Arabic (MTA) Part 1 (LDC2003T18)</a>. All source data for this corpus
is
newswire text. <o:p></o:p></p>
<p>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.<o:p></o:p></p>
<br>
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<pre class="moz-signature" cols="72"><big><font
face="Courier New, Courier, monospace"><small><small><big>Ilya Ahtaridis</big></small></small></font>
<font face="Courier New, Courier, monospace"><small><small><big>Membership Coordinator</big></small></small></font></big>
<font face="Courier New, Courier, monospace"><small>--------------------------------------------------------------------</small></font>
<font face="Courier New, Courier, monospace">Linguistic Data Consortium Phone: (215) 573-1275
University of Pennsylvania Fax: (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></font></pre>
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