cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35111/chqa-vd56
title: Nautilus Speaker Characterization

description: <h3>Introduction</h3><br>
<p>Nautilus Speaker Characterization was developed at the <a href="https://www.tu-berlin.de/menue/home/">Technical University of Berlin</a> and is comprised of approximately 155 hours of conversational speech from 300 German speakers aged 18 to 35 years (126 males and 174 females) with no marked dialect or accent, recorded in an acoustically-isolated room. The corpus was designed to support research on the detection of speaker social characteristics, such as personality, charisma and voice attractiveness.</p><br>
<p>Four scripted and four semi-spontaneous dialogs simulating telephone call inquiries were elicited from the speakers. Additionally, spontaneous neutral and emotional speech utterances (predominantly excitement or frustration) and questions were produced.</p><br>
<p>Speech corresponding to one of the semi-spontaneous dialogs was evaluated with respect to 34 continuous numeric labels of perceived interpersonal speaker characteristics (such as likable, attractive, competent, childish). For a set of 20 selected "extreme" speakers evaluated for their warmth-attractiveness, 34 naive voice descriptions (such as bright, creaky, articulate, melodious) were also evaluated.</p><br>
<h3>Data</h3><br>
<p>Interactions between speakers and their interlocutor (a recording assistant) are provided in separate mono files, accompanied by timestamps and tags that define the speaker's turns. Nearly all speech is sampled at 48 kHz, with some at 44.1 kHz. All speech files are 16-bit 1-channel flac compressed wav.</p><br>
<p>This release contains all labels, together with the speech recordings and the speakers' metadata (e.g., age, gender, place of birth, chronological places of residence and duration of stay, parents' place of birth, self-assessed personality).</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018S17.f.flac">female sample</a> and <a href="desc/addenda/LDC2018S17.m.flac">male sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 Laura Fernández Gallardo, © 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/qrtm-w130
title: DEFT Spanish Treebank

description: <h3>Introduction</h3><br>
<p>DEFT Spanish Treebank was developed by the Linguistic Data Consortium (LDC) and the <a href="http://clic.ub.edu/">Language and Computation Center (CLiC), University of Barcelona</a>. It contains treebank annotation of international Spanish newswire text and Latin American Spanish discussion forum data created for the DARPA Deep Exploration and Filtering of Text (DEFT) program.</p><br>
<p>DEFT aimed to improve state-of-the-art capabilities in automated deep natural language processing with a particular focus on technologies dealing with inference, casual relationships and anomaly detection across several languages. DEFT Spanish Treebank supported the program's goal of deep natural language understanding.</p><br>
<h3>Data</h3><br>
<p>Newswire source files were selected from Spanish Gigaword Third Edition (<a href="../../../ldc2011t12">LDC2011T12</a>) and were manually sentence-segmented for DEFT. Discussion forum source files were selected from Spanish discussion forum source data collected by LDC, consisting of continuous multi-posts of 100-1000 words.</p><br>
<p>This release contains 114 files (54,394 tokens) of newswire data and 60 files (55,307 tokens) of discussion forum data all of which were annotated with constituents and syntactic functions. The annotation guidelines for DEFT Spanish Treebank are included in the documentation accompanying this release.</p><br>
<p>Source documents are presented as plain text files with one sentence unit per line. Treebank annotation files are in xml.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T01.txt">source sample</a> and <a href="desc/addenda/LDC2018T01.xml">treebank sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.</p></br>
Portions © 1994-2001, 2004-2009 The Associated Press, © 2002, 2005, 2007, 2009-2010 Xinhua News Agency, © 2006, 2009, 2011, 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/n41t-3944
title: TRAD Chinese-French Parallel Text -- Blog

description: <h3>Introduction</h3><br>
<p>TRAD Chinese-French Parallel Text -- Blog was developed by <a href="http://elda.org/en/">ELDA</a> as part of the <a href="http://www.elra.info/en/projects/archived-projects/pea-trad/">PEA-TRAD project</a>. It contains French translations of a subset of approximately 10,000 Chinese words from GALE Phase 1 Chinese Blog Parallel Text (<a href="../../../LDC2008T06">LDC2008T06</a>).</p><br>
<p>The PEA-TRAD project (Translation as a Support for Document Analysis) was supported by the French Ministry of Defense (DGA). Its purpose was to develop speech-to-speech translation technology for multiple languages (e.g., Arabic, Chinese, Pashto) from a variety of domains. ELDA developed several corpora for this effort.</p><br>
<p>The Linguistic Data Consortium (LDC) has also released the following TRAD corpora:</p><br>
<ul><br>
<li>TRAD Arabic-French Parallel Text -- Newsgroup (<a href="../../../LDC2018T13">LDC2018T13</a>)</li><br>
<li>TRAD Chinese-French Parallel Text -- Broadcast News (<a href="../../../LDC2018T17">LDC2018T17</a>)</li><br>
<li>TRAD Arabic-French Parallel Text -- Newswire (<a href="../../../LDC2018T21">LDC2018T21</a>)</li><br>
</ul><br>
<h3>Data</h3><br>
<p>This release consists of 444 segments (translation units) from 17 documents. The source data is Chinese blog text collected and translated into English by LDC for the DARPA GALE (Global Autonomous Language Exploitation) program. Information about the ELDA translation team, translation guidelines and validation results is contained in the documentation accompanying this release.</p><br>
<p>The Chinese source file contains 15,809 characters and the French reference translation contains 11,769 words. The data is presented in two unicode-encoded XML files along with an associated DTD.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T02.src.xml">source sample</a> and <a href="desc/addenda/LDC2018T02.ref.xml">reference sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 ELDA, © 2005-2007, 2008, 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/3rxw-5114
title: TAC KBP Comprehensive English Source Corpora 2009-2014

description: <h3>Introduction</h3><br>
<p>TAC KBP Comprehensive English Source Corpora 2009-2014 was developed by the Linguistic Data Consortium (LDC) and contains the 3,877,207 English source documents used in support of the TAC KBP tasks from 2009-2014.</p><br>
<p>Text Analysis Conference (<a href="https://tac.nist.gov/">TAC</a>) is a series of workshops organized by the National Institute of Standards and Technology (<a href="https://www.nist.gov/">NIST</a>). TAC was developed to encourage research in natural language processing and related applications by providing a large test collection, common evaluation procedures, and a forum for researchers to share their results. Through its various evaluations, the Knowledge Base Population (KBP) track of TAC encourages the development of systems that can match entities mentioned in natural texts with those appearing in a knowledge base and extract novel information about entities from a document collection and add it to a new or existing knowledge base.</p><br>
<h3>Data</h3><br>
<p>The source data consists of newswire, broadcast material, and web text collected by LDC. Documents are released as a collection of zip files for overall compactness, and ease and efficiency of use. When unpacked the documents are all UTF-8 text files with a basic markup structure. Also provided are a series of lists and tables to aid in specific zip file to doc mappings and the recreation of specific test sets. See the included documentation for more information.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based on research sponsored by Air Force Research Laboratory and Defense Advance Research Projects Agency under agreement number FA8750-13-2-0045. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Air Force Research Laboratory and Defense Advanced Research Projects Agency or the U.S. Government.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T03.txt">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 1994-1997, 2001-2010 Agence France Presse, © 2005 Aljazeera, © 1996-1997 American Broadcasting Company, © 1994-2010 The Associated Press, © 1994-1997 Cable News Network, LP, LLLP, © 1997-1999, 2001, 2003-2010 Central News Agency (Taiwan), © 2005 Dubai TV, © 2005-2006 National Broadcasting Company, Inc., © 1996-1997 National Cable Satellite Corporation, © 1994-1998, 2003-2009 Los Angeles Times - Washington Post News Service, Inc., © 1994-2010 New York Times, © 1996-1997 Public Radio Iternational,© 1994-1995 Reuters America, Inc., © 1996 The University of California, USC Radio and Marketplace, © 2010 The Washington Post Service with Bloomberg News, © 1995-2010 Xinhua News Agency, © 1996-1998, 2007, 2011, 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/mtbt-9b85
title: H2, E2, ERK1 Children's Writing

description: <h3>Introduction</h3><br>
<p>H2, E2, ERK1 Children's Writing was developed by the <a href="http://www.dhbw.de/english/dhbw/about-us.html">Cooperative State University Baden-W&uuml;rttemberg</a>, University of Education. It consists of approximately 2,000 texts written over four months by 173 German school children age six through eleven years.</p><br>
<p>The data in this corpus was collected by elementary schools in Baden W&uuml;rttemberg, Germany and digitized at the Cooperative State University during the 2016/2017 school year. Three second, third, and fourth grade classrooms participated in the collection.</p><br>
<p>Texts were written within regular class settings. The students were presented with a picture and were asked to write a story, to describe the picture or if unable to write a text, to list what they saw in the picture. The pictures were designed to enhance the output with respect to important spelling error categories, namely, the marking of short vowels with a silent consonant letter and the correct spelling of the long vowel &lt;ie&gt;. The children were allowed at least 15 minutes to write the texts. This exercise was repeated weekly for nine or sixteen weeks depending on the program.</p><br>
<p>LDC has also released H1 Children's Writing (<a href="../../../LDC2016T01">LDC2016T01</a>).</p><br>
<h3>Data</h3><br>
<p>There were 173 total participants. 100 students were multilingual, and further metadata is available for 166 of the 173 children. The following is included for each text in the database: school week of collection; school type; age; gender; grade/classroom; language spoken at home; and school materials used.</p><br>
<p>In all, 2,117 texts representing 118,621 tokens were collected. The texts were digitized in two forms: (1) the original text, including all errors (achieved), and (2) the intended (target) text, where all spelling errors were removed. Annotations were added to both the achieved text and the target text to distinguish words that should not be analyzed for spelling errors, such as names or foreign words. For sentence-level analysis, syntax errors were annotated by marking substitutions, deletions and insertions at the word level. In such cases, the used word was analyzed for spelling, and the correct word was used for sentence structure analysis.</p><br>
<p>Original handwriting is presented as pdf documents and the converted text as UTF-8 plain text in csv documents.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T05.pdf">image sample</a> and <a href="desc/addenda/LDC2018T05.csv">transcript sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 Kay Berkling, Trustees of the University of Pennsylvania
DOI: 10.35111/eqzb-7x65
title: SPADE

description: <h3>Introduction</h3><br>
<p>SPADE (Syntactic Phrase Alignment Dataset for Evaluation) consists of annotated parse trees and alignment on English sentential paraphrases extracted from machine translation evaluation corpora and separated into development and test sets.</p><br>
<p>Reference translations from machine translation evaluation corpora were used as sentential paraphrases. They were sourced from the following data sets released by LDC from the NIST (National Institute of Standards and Technology) open machine translation evaluation series (<a href="https://www.nist.gov/itl/iad/mig/open-machine-translation-evaluation">OpenMT</a>): <a href="../../../LDC2010T14">LDC2010T14</a>, <a href="../../../LDC2010T17">LDC2010T17</a>, <a href="../../../LDC2010T21">LDC2010T21</a>, and <a href="../../../LDC2013T03">LDC2013T03</a>.</p><br>
<h3>Data</h3><br>
<p>Reference translations of 10 to 30 words were randomly extracted for annotation from NIST OpenMT corpora. Gold standard annotations of HPSG (head-driven phrase structure grammar) trees and phrase alignments were performed, resulting in 20,276 phrases extracted from 201 sentential paraphrases and 15,721 paraphrase alignments. Further information about the annotation process is contained in the documentation accompanying this release.</p><br>
<p>All annotation data is presented as UTF-8 XML.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T09.xml">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 Yuki Arase, © 2005-2007, 2009-2011, 2013, 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/9fjp-2a75
title: BOLT Arabic Discussion Forums

description: <h3>Introduction</h3><br>
<p>BOLT Arabic Discussion Forums was developed by the Linguistic Data Consortium (LDC) and consists of 813,080 discussion forum threads in Egyptian Arabic harvested from the Internet using a combination of manual and automatic processes.</p><br>
<p>The DARPA <a href="https://www.ldc.upenn.edu/collaborations/current-projects/bolt">BOLT</a> (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 material in this release represents the unannotated Arabic source data in the discussion forum genre.</p><br>
<h3>Data</h3><br>
<p>Collection was seeded based on the results of manual data scouting by native speaker annotators. Scouts were instructed to seek content in Egyptian Arabic that was original, interactive and informal. Upon locating an appropriate thread, scouts submitted the URL and some simple judgments about it to a database, via a web browser plug-in. When multiple threads from a forum were submitted, the entire forum was automatically harvested and added to the collection. The scale of the collection precluded manual review of all data. Only a small portion of the threads included in this release were manually reviewed, and it is expected that there may be some offensive or otherwise undesired content as well as some threads that contain a large amount of non-Arabic content. Language identification was performed on all threads in this corpus (using <a href="https://github.com/CLD2Owners/cld2">CLD2</a>), and threads for which the results indicate a high probability of largely non-Arabic content are listed in arz_suspect_LID.txt in the docs directory of this package. It should also be noted that many threads may contain a mixture of Egyptian and other varieties of Arabic, even among the threads that are primarily Arabic.</p><br>
<p>The corpus is comprised of zipped HTML and XML files. The HTML files are a raw HTML file downloaded from the discussion thread. If the thread spanned multiple URLs, it was stored as a concatenation of the downloaded HTML files. The XML files were converted from the raw HTML.</p><br>
<p> </p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T10.html">html sample</a> and <a href="desc/addenda/LDC2018T10.xml">xml sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/55s4-ym31
title: TRAD Arabic-French Parallel Text -- Newsgroup

description: <h3>Introduction</h3><br>
<p>TRAD Arabic-French Parallel Text -- Newsgroup was developed by <a href="http://elda.org/en/">ELDA</a> as part of the <a href="http://www.elra.info/en/projects/archived-projects/pea-trad/">PEA-TRAD project</a>. It contains French translations of a subset of approximately 10,000 Arabic words from GALE Phase 1 Arabic Newsgroup Parallel Text - Part 1 (<a href="../../../LDC2009T03">LDC2009T03</a>).</p><br>
<p>The PEA-TRAD project (Translation as a Support for Document Analysis) was supported by the French Ministry of Defense (DGA). Its purpose was to develop speech-to-speech translation technology for multiple languages (e.g., Arabic, Chinese, Pashto) from a variety of domains. ELDA developed several corpora for this effort.</p><br>
<p>The Linguistic Data Consortium (LDC) has also released the following TRAD corpora:</p><br>
<ul><br>
<li>TRAD Chinese-French Parallel Text -- Blog (<a href="../../../LDC2018T02">LDC2018T02</a>)</li><br>
<li>TRAD Chinese-French Parallel Text -- Broadcast News (<a href="../../../LDC2018T17">LDC2018T17</a>)</li><br>
<li>TRAD Arabic-French Parallel Text -- Newswire (<a href="../../../LDC2018T21">LDC2018T21</a>)</li><br>
</ul><br>
<h3>Data</h3><br>
<p>This release consists of 398 segments (translation units) from 17 documents. The source data is Arabic newsgroup text collected and translated into English by the Linguistic Data Consortium for the DARPA GALE (Global Autonomous Language Exploitation) program. Information about the ELDA translation team, translation guidelines and validation results is contained in the documentation accompanying this release.</p><br>
<p>The Arabic source file contains 10,706 words and the French reference translation contains 15,843 words. The data is presented in two unicode-encoded XML files along with an associated DTD.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T13.src.xml">source sample</a> and <a href="desc/addenda/LDC2018T13.ref.xml">reference sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 ELDA, © 2005-2007, 2009, 2018 Trustees of the University of Pennsylvania
DOI: 10.35111/1whw-ea40
title: BOLT Chinese SMS/Chat

description: <h3>Introduction</h3><br>
<p>BOLT Chinese SMS/Chat was developed by the Linguistic Data Consortium (LDC) and consists of naturally-occurring Short Message Service (SMS) and Chat (CHT) data collected through data donations and live collection involving native speakers of Chinese. The corpus contains 14,877 conversations totaling 3,005,810 words across 497,543 messages.</p><br>
<p>The <a href="https://www.ldc.upenn.edu/collaborations/current-projects/bolt">BOLT</a> (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.</p><br>
<h3>Data</h3><br>
<p>The data in this release was collected using two methods: new collection via LDC's collection platform, and donation of SMS or chat archives from BOLT collection participants. All data collected were reviewed manually to exclude any messages/conversations that were not in the target language or that had sensitive content, such as personal identifying information (PII). All data is presented in UTF-8 XML.</p><br>
<h3>Acknowledgement</h3><br>
<p>This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-11-C-0145. The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.</p><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T15.xml">sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
Portions © 2018 Trustees of the University of Pennsylvania