Paper Info
Title
Towards A Multimodal Meeting Record
Abstract
Face-to-face meetings usually encompass several modalities including speech, gesture, handwriting, and person identification. Recognition and integration of each of these modalities is important to create an accurate record of a meeting. However, each of these modalities presents recognition difficulties. Speech recognition must be speaker and domain independent, have low word error rates, and be close to real time to be useful. Gesture and handwriting recognition must be writer independent and support a wide variety of writing styles. Person identification has difficulty with segmentation in a crowded room. Furthermore, in order to produce the record automatically, we have to solve the assignment problem (who is saying what), which involves people identification and speech recognition. This paper will examine a multimodal meeting room system under development at Carnegie Mellon University that enables us to track, capture and integrate the important aspects of a meeting from people identification to meeting transcription. Once a multimedia meeting record is created, it can be archived for later retrieval.
Year
DOI
Venue
2000
10.1109/ICME.2000.871074
2000 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, PROCEEDINGS VOLS I-III
Keywords
Field
DocType
groupware,speech recognition,speech,writing styles,automatic speech recognition,word error rate,writing,face recognition,assignment problem,real time,gesture,nist,handwriting recognition,speaker recognition
Handwriting,Gesture,Computer science,Handwriting recognition,Gesture recognition,Human–computer interaction,Speaker recognition,Face Recognition Grand Challenge,Artificial intelligence,Computer vision,Intelligent character recognition,Sketch recognition,Multimedia
Conference
Citations 
PageRank 
References 
12
1.29
8
Authors
7
Name
Order
Citations
PageRank
Ralph Gross128114.80
Michael Bett217019.15
Hua Yu3121.29
Xiaojin Zhu43586222.74
Yue Pan5121.29
Jie Yang62856270.24
Alex Waibel763431980.68