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    • Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences. (9)
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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 9 of 9 1 A computational model to connect gestalt perception and natural language Dhande, Sheel Sanjay, 1979-. - : Massachusetts Institute of Technology, 2003 BASE Show details 2 Singing voice analysis/synthesis Kim, Youngmoo E. - : Massachusetts Institute of Technology, 2003 BASE Show details 3 Spontaneous speech recognition using visual context-aware language models Mukherjee, Niloy, 1978-. - : Massachusetts Institute of Technology, 2003 Abstract: Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003. ; Includes bibliographical references (p. 83-88). ; The thesis presents a novel situationally-aware multimodal spoken language system called Fuse that performs speech understanding for visual object selection. An experimental task was created in which people were asked to refer, using speech alone, to objects arranged on a table top. During training, Fuse acquires a grammar and vocabulary from a "show-and-tell" procedure in which visual scenes are paired with verbal descriptions of individual objects. Fuse determines a set of visually salient words and phrases and associates them to a set of visual features. Given a new scene, Fuse uses the acquired knowledge to generate class-based language models conditioned on the objects present in the scene as well as a spatial language model that predicts the occurrences of spatial terms conditioned on target and landmark objects. The speech recognizer in Fuse uses a weighted mixture of these language models to search for more likely interpretations of user speech in context of the current scene. During decoding, the weights are updated using a visual attention model which redistributes attention over objects based on partially decoded utterances. The dynamic situationally-aware language models enable Fuse to jointly infer spoken language utterances underlying speech signals as well as the identities of target objects they refer to. In an evaluation of the system, visual situationally-aware language modeling shows significant , more than 30 %, decrease in speech recognition and understanding error rates. The underlying ideas of situation-aware speech understanding that have been developed in Fuse may may be applied in numerous areas including assistive and mobile human-machine interfaces. ; by Niloy Mukherjee. ; S.M. Keyword: Architecture. Program In Media Arts and Sciences URL: http://hdl.handle.net/1721.1/62380 BASE Hide details 4 Full-contact poetry Basu, Anindita, 1978-. - : Massachusetts Institute of Technology, 2002 BASE Show details 5 Non-verbal signals for grounding in embodied conversational agent Nakano, Yukiko I., 1963-. - : Massachusetts Institute of Technology, 2002 BASE Show details 6 Telling tales : a new way to encourage written literacy through oral language ; New way to encourage written literacy through oral language Ananny, Michael J. (Michael Joseph), 1976-. - : Massachusetts Institute of Technology, 2001 BASE Show details 7 Design for very large-scale conversations Sack, Warren. - : Massachusetts Institute of Technology, 2000 BASE Show details 8 Paired speech and gesture generation in embodied conversational agents Yan, Hao, 1973-. - : Massachusetts Institute of Technology, 2000 BASE Show details 9 The linguistic exploration of children : playing with language through computer programming ; Playing with language through computer programming Vaikakul, Savalai, 1976-. - : Massachusetts Institute of Technology, 1999 BASE Show details

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