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The AMI Meeting Corpus: a Pre-Announcement
Type of publication: Conference paper
Citation: carletta:mlmi05
Booktitle: Machine Learning for Multimodal Interaction: Second International Workshop, MLMI'2005
Year: 2005
Crossref: guillemo:rr05-82:
Abstract: The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. It is being created in the context of a project that is developing meeting browsing technology and will eventually be released publicly. Some of the meetings it contains are naturally occurring, and some are elicited, particularly using a scenario in which the participants play different roles in a design team, taking a design project from kick-off to completion over the course of a day. The corpus is being recorded using a wide range of devices including close-talking and far-field microphones, individual and room-view video cameras, projection, a whiteboard, and individual pens, all of which produce output signals that are synchronized with each other. It is also being hand-annotated for many different phenomena, including orthographic transcription, discourse properties such as named entities and dialogue acts, summaries, emotions, and some head and hand gestures. We describe the data set, including the rationale behind using elicited material, and explain how the material is being recorded, transcribed and annotated.
Userfields: ipdmembership={speech, learning, vision},
Keywords:
Projects Idiap
Authors Carletta, Jean
Ashby, Simone
Bourban, Sebastien
Flynn, Mike
Guillemot, Maël
Hain, Thomas
Kadlec, Jaroslav
Karaiskos, Vasilis
Kraaij, Wessel
Kronenthal, Melissa
Lathoud, Guillaume
Lincoln, Mike
Lisowska, Agnes
McCowan, Iain A.
Post, Wilfried
Reidsma, Dennis
Wellner, Pierre
Added by: [UNK]
Total mark: 0
Attachments
  • carletta-2005-mlmi.pdf
  • guillemo-idiap-rr-05-82.ps.gz
Notes