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ORCIDMturk@HLT-NAACL 2010: Los Angeles, USA
- Chris Callison-Burch, Mark Dredze:
Proceedings of the 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk, Los Angeles, USA, June 6, 2010. Association for Computational Linguistics 2010 - Chris Callison-Burch, Mark Dredze:
Creating Speech and Language Data With Amazon's Mechanical Turk. 1-12 - Mukund Jha, Jacob Andreas, Kapil Thadani, Sara Rosenthal, Kathleen R. McKeown:
Corpus Creation for New Genres: A Crowdsourced Approach to PP Attachment. 13-20 - Gabriel Parent, Maxine Eskénazi:
Clustering dictionary definitions using Amazon Mechanical Turk. 21-29 - Qin Gao, Stephan Vogel:
Semi-supervised Word Alignment with Mechanical Turk. 30-34 - Michael Heilman, Noah A. Smith:
Rating Computer-Generated Questions with Mechanical Turk. 35-40 - Scott Novotney, Chris Callison-Burch:
Crowdsourced Accessibility: Elicitation of Wikipedia Articles. 41-44 - Audrey N. Le, Jerome Ajot, Mark A. Przybocki, Stephanie M. Strassel:
Document Image Collection Using Amazon's Mechanical Turk. 45-52 - Keelan Evanini, Derrick Higgins, Klaus Zechner:
Using Amazon Mechanical Turk for Transcription of Non-Native Speech. 53-56 - Michael J. Denkowski, Alon Lavie:
Exploring Normalization Techniques for Human Judgments of Machine Translation Adequacy Collected Using Amazon Mechanical Turk. 57-61 - Vamshi Ambati, Stephan Vogel:
Can Crowds Build parallel corpora for Machine Translation Systems? 62-65 - Michael J. Denkowski, Hassan Al-Haj, Alon Lavie:
Turker-Assisted Paraphrasing for English-Arabic Machine Translation. 66-70 - Nolan Lawson, Kevin Eustice, Mike Perkowitz, Meliha Yetisgen-Yildiz:
Annotating Large Email Datasets for Named Entity Recognition with Mechanical Turk. 71-79 - Tim Finin, William Murnane, Anand Karandikar, Nicholas Keller, Justin Martineau, Mark Dredze:
Annotating Named Entities in Twitter Data with Crowdsourcing. 80-88 - Chiara Higgins, Elizabeth McGrath, Laila Moretto:
MTurk Crowdsourcing: A Viable Method for Rapid Discovery of Arabic Nicknames? 89-92 - Omar Zaidan, Juri Ganitkevitch:
An Enriched MT Grammar for Under $100. 93-98 - Matthew Marge, Satanjeev Banerjee, Alexander I. Rudnicky:
Using the Amazon Mechanical Turk to Transcribe and Annotate Meeting Speech for Extractive Summarization. 99-107 - Ann Irvine, Alexandre Klementiev:
Using Mechanical Turk to Annotate Lexicons for Less Commonly Used Languages. 108-113 - Bart Mellebeek, Francesc Benavent, Jens Grivolla, Joan Codina, Marta R. Costa-jussà, Rafael E. Banchs:
Opinion Mining of Spanish Customer Comments with Non-Expert Annotations on Mechanical Turk. 114-121 - Robert Munro, Steven Bethard, Victor Kuperman, Vicky Tzuyin Lai, Robin Melnick, Christopher Potts, Tyler Schnoebelen, Harry J. Tily:
Crowdsourcing and language studies: the new generation of linguistic data. 122-130 - Jonathan Chang:
Not-So-Latent Dirichlet Allocation: Collapsed Gibbs Sampling Using Human Judgments. 131-138 - Cyrus Rashtchian, Peter Young, Micah Hodosh, Julia Hockenmaier:
Collecting Image Annotations Using Amazon's Mechanical Turk. 139-147 - Dan Gillick, Yang Liu:
Non-Expert Evaluation of Summarization Systems is Risky. 148-151 - Tae Yano, Philip Resnik, Noah A. Smith:
Shedding (a Thousand Points of) Light on Biased Language. 152-158 - Jonathan Gordon, Benjamin Van Durme, Lenhart K. Schubert:
Evaluation of Commonsense Knowledge with Mechanical Turk. 159-162 - Rui Wang, Chris Callison-Burch:
Cheap Facts and Counter-Facts. 163-167 - Stephen A. Kunath, Steven H. Weinberger:
The Wisdom of the Crowdâs Ear: Speech Accent Rating and Annotation with Amazon Mechanical Turk. 168-171 - Catherine Grady, Matthew Lease:
Crowdsourcing Document Relevance Assessment with Mechanical Turk. 172-179 - Meliha Yetisgen-Yildiz, Imre Solti, Fei Xia, Scott R. Halgrim:
Preliminary Experiments with Amazon's Mechanical Turk for Annotating Medical Named Entities. 180-183 - Ian R. Lane, Matthias Eck, Kay Rottmann, Alex Waibel:
Tools for Collecting Speech Corpora via Mechanical-Turk. 184-187 - Nitin Madnani, Jordan L. Boyd-Graber, Philip Resnik:
Measuring Transitivity Using Untrained Annotators. 188-194 - Cem Akkaya, Alexander Conrad, Janyce Wiebe, Rada Mihalcea:
Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation. 195-203 - Matthew R. Gormley, Adam Gerber, Mary P. Harper, Mark Dredze:
Non-Expert Correction of Automatically Generated Relation Annotations. 204-207 - Michael Bloodgood, Chris Callison-Burch:
Using Mechanical Turk to Build Machine Translation Evaluation Sets. 208-211 - Matteo Negri, Yashar Mehdad:
Creating a Bi-lingual Entailment Corpus through Translations with Mechanical Turk: $100 for a 10-day Rush. 212-216 - Olivia Buzek, Philip Resnik, Ben Bederson:
Error Driven Paraphrase Annotation using Mechanical Turk. 217-221
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