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The AMI Meeting Corpus: A Pre-announcement

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 3869)

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.

Keywords

  • Design Team
  • Acoustic Model
  • Industrial Designer
  • Marketing Expert
  • Pronunciation Variation

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This work was supported by the European Union 6th FWP IST Integrated Project AMI (Augmented Multi-party Interaction, FP6-506811).

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Carletta, J. et al. (2006). The AMI Meeting Corpus: A Pre-announcement. In: Renals, S., Bengio, S. (eds) Machine Learning for Multimodal Interaction. MLMI 2005. Lecture Notes in Computer Science, vol 3869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11677482_3

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  • DOI: https://doi.org/10.1007/11677482_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32549-9

  • Online ISBN: 978-3-540-32550-5

  • eBook Packages: Computer ScienceComputer Science (R0)