Paper
25 April 1995 Automated speech understanding: the next generation
J. Picone, W. J. Ebel, N. Deshmukh
Author Affiliations +
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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J. Picone, W. J. Ebel, and N. Deshmukh "Automated speech understanding: the next generation", Proc. SPIE 10279, Digital Signal Processing Technology: A Critical Review, 1027907 (25 April 1995); https://doi.org/10.1117/12.204212
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Cited by 1 scholarly publication and 1 patent.
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KEYWORDS
Digital signal processing

Signal processing

Internet

Mathematics

Pattern recognition

Statistical analysis

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