Maël Guillemot

The AMI meeting corpus: a pre-announcement

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-o 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.

Browsing recorded meetings with ferret

Browsing for elements of interest within a recorded meeting is time-consuming. We describe work in progress on a meeting browser, which aims to support this process by displaying many types of data. These include media, transcripts and processing results such as speaker segmentations. Users interact with these visualizations to observe and control synchronized playback of the recorded meeting.

Spectral structuring of home videos

Accessing and organizing home videos present technical challenges due to their unrestricted content and lack of storyline. In this paper, we propose a spectral method to group video shots into scenes based on their visual similarity and temporal relations. Spectral methods have been shown to be effective in capturing perceptual organization features. In particular, we investigate the problem of automatic model selection, which is currently an open research issue for spectral methods, and propose measures to assess the validity of a grouping result. The methodology is used to group scenes from a six-hour home video database, and is assessed with respect to a ground-truth generated by multiple people. The results indicate the validity of the proposed approach, both compared to existing techniques as well as the human ground-truth.

Klewel Webcast: From Research to Growing Company

The main motivations behind the webcasting company, Klewel, were to go beyond text-based conference proceedings to offer a user-friendly way to browse and replay presentations, access slides, and search for specific information within a recording. As the project got under way, the team came together, and eventually an innovative webcasting solution saw the light of day. Learn how the company moved from research to technology by focusing on multidisciplinary research, early real-world prototyping and testing, collaboration, and client needs.