2026-09-20T08:41:33Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/297252022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Deb Roy.
Yoshida, Norimasa, 1979-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-03-24T16:19:41Z
2006-03-24T16:19:41Z
2002
2002
http://hdl.handle.net/1721.1/29725
54038711
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
Includes bibliographical references (p. 79-80).
As applications incorporating speech recognition technology become widely used, it is desireable to have such systems interact naturally with its users. For such natural interaction to occur, recognition systems must be able to accurately detect when a speaker has finished speaking. This research presents an analysis combining lower and higher level cues to perform the utterance endpointing task. The analysis involves obtaining the optimal parameters for the signal level utterance segmenter, a component of the speech recognition system in the Cognitive Machines Group, and exploring the incorporation of pause duration and grammar information to the utterance segmentation task. As a result, we obtain an optimal set of parameters for the lower level utterance segmenter, and show that part-of-speech based N-gram language modeling of the spoken words in conjunction with pause duration can provide effective signals for utterance endpointing.
b y Norimasa Yoshida.
M.Eng.
80 p.
2868623 bytes
2868427 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Automatic utterance segmentation in spontaneous speech
Thesis
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