SOUP: A Parser for Real-world Spontaneous Speech

Marsal Gavaldà


Abstract
This paper describes the key features of SOUP, a stochastic, chart-based, top-down parser, especially engineered for real-time analysis of spoken language with very large, multi-domain semantic grammars. SOUP achieves flexibility by encoding context-free grammars, specified for example in the Java Speech Grammar Format, as probabilistic recursive transition networks, and robustness by allowing skipping of input words at any position and producing ranked interpretations that may consist of multiple parse trees. Moreover, SOUP is very efficient, which allows for practically instantaneous backend response.
Anthology ID:
2000.iwpt-1.12
Volume:
Proceedings of the Sixth International Workshop on Parsing Technologies
Month:
February 23-25
Year:
2000
Address:
Trento, Italy
Editors:
Alberto Lavelli, John Carroll, Robert C. Berwick, Harry C. Bunt, Bob Carpenter, John Carroll, Ken Church, Mark Johnson, Aravind Joshi, Ronald Kaplan, Martin Kay, Bernard Lang, Alon Lavie, Anton Nijholt, Christer Samuelsson, Mark Steedman, Oliviero Stock, Hozumi Tanaka, Masaru Tomita, Hans Uszkoreit, K. Vijay-Shanker, David Weir, Mats Wiren
Venue:
IWPT
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
101–110
Language:
URL:
https://aclanthology.org/2000.iwpt-1.12
DOI:
Bibkey:
Cite (ACL):
Marsal Gavaldà. 2000. SOUP: A Parser for Real-world Spontaneous Speech. In Proceedings of the Sixth International Workshop on Parsing Technologies, pages 101–110, Trento, Italy. Association for Computational Linguistics.
Cite (Informal):
SOUP: A Parser for Real-world Spontaneous Speech (Gavaldà, IWPT 2000)
Copy Citation:
PDF:
https://aclanthology.org/2000.iwpt-1.12.pdf