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Proceedings Paper

Automated speech understanding: the next generation
Author(s): J. Picone; W. J. Ebel; N. Deshmukh
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Paper Abstract

Modern speech understanding systems merge interdisciplinary technologies from Signal Processing, Pattern Recognition, Natural Language, and Linguistics into a unified statistical framework. These systems, which have applications in a wide range of signal processing problems, represent a revolution in Digital Signal Processing (DSP). Once a field dominated by vector-oriented processors and linear algebra-based mathematics, the current generation of DSP-based systems rely on sophisticated statistical models implemented using a complex software paradigm. Such systems are now capable of understanding continuous speech input for vocabularies of several thousand words in operational environments. The current generation of deployed systems, based on small vocabularies of isolated words, will soon be replaced by a new technology offering natural language access to vast information resources such as the Internet, and provide completely automated voice interfaces for mundane tasks such as travel planning and directory assistance.

Paper Details

Date Published: 25 April 1995
PDF: 14 pages
Proc. SPIE 10279, Digital Signal Processing Technology: A Critical Review, 1027907 (25 April 1995); doi: 10.1117/12.204212
Show Author Affiliations
J. Picone, Mississippi State Univ. (United States)
W. J. Ebel, Mississippi State Univ. (United States)
N. Deshmukh, Boston Univ. (United States)


Published in SPIE Proceedings Vol. 10279:
Digital Signal Processing Technology: A Critical Review
Panos Papamichalis; Robert D. Kerwin, Editor(s)

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