Sunday, June 6, 2010 9:00am Morning SessionCreating Speech and Language Data With Amazon’s Mechanical Turk Chris Callison-Burch and Mark Dredze 9:10am Invited Talk by CrowdFlower 10:10am Morning Presentation Session Corpus Creation for New Genres: A Crowdsourced Approach to PP Attachment Mukund Jha, Jacob Andreas, Kapil Thadani, Sara Rosenthal and Kathleen McKeown 10:30am Break 11:00am Morning Poster Session Note: morning talks will also be presented as posters in this session. Clustering dictionary definitions using Amazon Mechanical Turk Gabriel Parent and Maxine Eskenazi Semi-supervised Word Alignment with Mechanical Turk Qin Gao and Stephan Vogel Rating Computer-Generated Questions with Mechanical Turk Michael Heilman and Noah A. Smith Crowdsourced Accessibility: Elicitation of Wikipedia Articles Scott Novotney and Chris Callison-Burch Document Image Collection Using Amazon’s Mechanical Turk Audrey Le, Jerome Ajot, Mark Przybocki and Stephanie Strassel Using Amazon Mechanical Turk for Transcription of Non-Native Speech Keelan Evanini, Derrick Higgins and Klaus Zechner Exploring Normalization Techniques for Human Judgments of Machine Translation Adequacy Collected Using Amazon Mechanical Turk Michael Denkowski and Alon Lavie Can Crowds Build parallel corpora for Machine Translation Systems? Vamshi Ambati and Stephan Vogel Turker-Assisted Paraphrasing for English-Arabic Machine Translation Michael Denkowski, Hassan Al-Haj and Alon Lavie Annotating Large Email Datasets for Named Entity Recognition with Mechanical Turk Nolan Lawson, Kevin Eustice, Mike Perkowitz and Meliha Yetisgen-Yildiz Annotating Named Entities in Twitter Data with Crowdsourcing Tim Finin, William Murnane, Anand Karandikar, Nicholas Keller, Justin Martineau and Mark Dredze MTurk Crowdsourcing: A Viable Method for Rapid Discovery of Arabic Nicknames? Chiara Higgins, Elizabeth McGrath and Laila Moretto An Enriched MT Grammar for Under $100 Omar Zaidan and Juri Ganitkevitch 12:30pm Lunch 1:30pm Afternoon Presentation Session 1 Using the Amazon Mechanical Turk to Transcribe and Annotate Meeting Speech for Extractive Summarization Matthew Marge, Satanjeev Banerjee and Alexander Rudnicky Using Mechanical Turk to Annotate Lexicons for Less Commonly Used Languages Ann Irvine and Alexandre Klementiev Opinion Mining of Spanish Customer Comments with Non-Expert Annotations on Mechanical Turk Bart Mellebeek, Francesc Benavent, Jens Grivolla, Joan Codina, Marta R. Costa-Jussà and Rafael Banchs Crowdsourcing and language studies: the new generation of linguistic data Robert Munro, Steven Bethard, Victor Kuperman, Vicky Tzuyin Lai, Robin Melnick, Christopher Potts, Tyler Schnoebelen and Harry Tily Not-So-Latent Dirichlet Allocation: Collapsed Gibbs Sampling Using Human Judgments Jonathan Chang 3:10pm Break 3:30pm Afternoon Presentation Session 2 Collecting Image Annotations Using Amazon’s Mechanical Turk Cyrus Rashtchian, Peter Young, Micah Hodosh and Julia Hockenmaier Non-Expert Evaluation of Summarization Systems is Risky Dan Gillick and Yang Liu Shedding (a Thousand Points of) Light on Biased Language Tae Yano, Philip Resnik and Noah A. Smith 4:30pm Afternoon Poster Session Note: afternoon talks will also be presented as posters in this session. Evaluation of Commonsense Knowledge with Mechanical Turk Jonathan Gordon, Benjamin Van Durme and Lenhart Schubert Cheap Facts and Counter-Facts Rui Wang and Chris Callison-Burch The Wisdom of the Crowds Ear: Speech Accent Rating and Annotation with Amazon Mechanical Turk Stephen Kunath and Steven Weinberger Crowdsourcing Document Relevance Assessment with Mechanical Turk Catherine Grady and Matthew Lease Preliminary Experiments with Amazon’s Mechanical Turk for Annotating Medical Named Entities Meliha Yetisgen-Yildiz, Imre Solti, Fei Xia and Scott Halgrim Tools for Collecting Speech Corpora via Mechanical-Turk Ian Lane, Matthias Eck, Kay Rottmann and Alex Waibel Measuring Transitivity Using Untrained Annotators Nitin Madnani, Jordan Boyd-Graber and Philip Resnik Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation Cem Akkaya, Alexander Conrad, Janyce Wiebe and Rada Mihalcea Non-Expert Correction of Automatically Generated Relation Annotations Matthew R. Gormley, Adam Gerber, Mary Harper and Mark Dredze Using Mechanical Turk to Build Machine Translation Evaluation Sets Michael Bloodgood and Chris Callison-Burch Creating a Bi-lingual Entailment Corpus through Translations with Mechanical Turk: $100 for a 10-day Rush Matteo Negri and Yashar Mehdad Error Driven Paraphrase Annotation using Mechanical Turk Olivia Buzek, Philip Resnik and Ben Bederson |