Sébastien Cuendet

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We analyze classroom orchestration as a question of usability in which the classroom is the user. Our experiments revealed design features that reduce the global orchestration load. According to our studies in vocational schools, paper-based interfaces have the potential of making educational workflows tangible, i.e. both visible and manipulable. Our(More)
Spontaneous speech differs in a multitude of ways from read, formal, or laboratory speech (Maclay & Osgood 1959, Goldman-Eisler 1968, Levelt 1983, Biber 1988, Howell & Kadi-Hanifi 1991, Eskenazi 1993, Shriberg 1994, Swerts et al. 1996, Bruce 1995, Hirschberg 1995, Laan 1997). Although the labels “spontaneous” and “read” each reflect an underlying(More)
This paper analyzes various methods to adapt sentence segmentation models trained on conversational telephone speech (CTS) to meeting style conversations. The sentence segmentation model trained using a large amount of CTS data is used to improve the performance when various amounts of meeting data are available. We test the sentence segmentation(More)
There are many speech and language processing problems which require cascaded classification tasks. While model adaptation has been shown to be useful in isolated speech and language processing tasks, it is not clear what constitutes system adaptation for such complex systems. This paper studies the following questions: In cases where a sequence of(More)
Information retrieval techniques for speech are based on those developed for text, and thus expect structured data as input. An essential task is to add sentence boundary information to the otherwise unannotated stream of words output by automatic speech recognition systems. We analyze sentence segmentation performance as a function of feature types and(More)
Designing ICT systems for rural users in the developing world is difficult for a variety of reasons ranging from problems with infrastructure to wide differences in user contexts and capabilities. Developing regions may include huge variability in spoken languages, and users are often low- or non-literate, with very little experience interacting with(More)
We investigate the application of the co-training learning algorithm on the sentence boundary classification problem by using lexical and prosodic information. Co-training is a semisupervised machine learning algorithm that uses multiple weak classifiers with a relatively small amount of labeled data and incrementally uses unlabeled data. The assumption in(More)
Automatic sentence segmentation of spoken language is an important precursor to downstream natural language processing. Previous studies combine lexical and prosodic features, but can impose significant computational challenges because of the large size of feature sets. Little is understood about which features most benefit performance, particularly for(More)
Tangible User Interfaces (TUIs) offer the potential to facilitate collaborative learning in new ways. This paper presents an empirical study that investigated the effects of a TUI in a classroom setting on task performance and learning outcomes. In the tangible condition, apprentices worked together around an interactive tabletop warehouse simulation using(More)