Summary of the paper

Title The Twins Corpus of Museum Visitor Questions
Authors Priti Aggarwal, Ron Artstein, Jillian Gerten, Athanasios Katsamanis, Shrikanth Narayanan, Angela Nazarian and David Traum
Abstract The Twins corpus is a collection of utterances spoken in interactions with two virtual characters who serve as guides at the Museum of Science in Boston. The corpus contains about 200,000 spoken utterances from museum visitors (primarily children) as well as from trained handlers who work at the museum. In addition to speech recordings, the corpus contains the outputs of speech recognition performed at the time of utterance as well as the system interpretation of the utterances. Parts of the corpus have been manually transcribed and annotated for question interpretation. The corpus has been used for improving performance of the museum characters and for a variety of research projects, such as phonetic-based Natural Language Understanding, creation of conversational characters from text resources, dialogue policy learning, and research on patterns of user interaction. It has the potential to be used for research on children's speech and on language used when talking to a virtual human.
Topics Corpus (creation, annotation, etc.), Speech resource/database, Dialogue
Full paper The Twins Corpus of Museum Visitor Questions
Bibtex @InProceedings{AGGARWAL12.595,
  author = {Priti Aggarwal and Ron Artstein and Jillian Gerten and Athanasios Katsamanis and Shrikanth Narayanan and Angela Nazarian and David Traum},
  title = {The Twins Corpus of Museum Visitor Questions},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }
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