Summary of the paper

Title Collecting Voices from the Cloud
Authors Ian McGraw, Chia-ying Lee, Lee Hetherington, Stephanie Seneff and Jim Glass
Abstract The collection and transcription of speech data is typically an expensive andtime-consuming task. Voice over IP and cloud computing are poised to greatlyreduce this impediment to research on spoken language interfaces in manydomains. This paper documents our efforts to deploy speech-enabled webinterfaces to large audiences over the Internet via Amazon Mechanical Turk, anonline marketplace for work. Using the open source WAMI Toolkit, we collectedcorpora in two different domains which collectively constitute over 113 hoursof speech. The first corpus contains 100,000 utterances of read speech, andwas collected by asking workers to record street addresses in the UnitedStates. For the second task, we collected conversations with FlightBrowser, amultimodal spoken dialogue system. The FlightBrowser corpus obtained contains10,651 utterances composing 1,113 individual dialogue sessions from 101distinct users. The aggregate time spent collecting the data for both corporawas just under two weeks. At times, our servers were logging audio fromworkers at rates faster than real-time. We describe the process of collectionand transcription of these corpora while providing an analysis of theadvantages and limitations to this data collection method.
Language Speech Recognition/Understanding
Topics Corpus (creation, annotation, etc.), Speech resource/database, Speech Recognition/Understanding
Full paper Collecting Voices from the Cloud
Bibtex @InProceedings{MCGRAW10.822,
  author = {Ian McGraw, Chia-ying Lee, Lee Hetherington, Stephanie Seneff and Jim Glass},
  title = {Collecting Voices from the Cloud},
  booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
 }
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