A stochastic parts program and noun phrase parser for unrestricted text

Author

Church, Kemth Ward

Author_Institution

Bell Lab., Murray Hill, NJ, USA

fYear

1989

Firstpage

695

Abstract

A program that tags each word in an input sentence with the most likely part of speech has been written. The program uses a linear-time dynamic programming algorithm to find an assignment of parts of speech to words that optimizes the product of (a) lexical probabilities (probability of observing part of speech i given word i) and (b) contextual probabilities (probability of observing part of speech i given n following parts of speech). Program performance is encouraging; a 400-word sample is presented and is judged to be 99.5% correct

Keywords

speech analysis and processing; speech recognition; contextual probabilities; input sentence; lexical probabilities; linear-time dynamic programming algorithm; noun phrase parser; program performance; stochastic parts program; unrestricted text; Filters; Lattices; Natural languages; Optical character recognition software; Speech analysis; Speech recognition; Speech synthesis; Stochastic processes; Synthesizers; Tagging;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on

Conference_Location

Glasgow

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1989.266522

Filename

266522

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1560981