Soup: a parser for real-world spontaneous speech

Authors:
Marsal Gavaldà
Affiliations:
Interactive Systems, Carnegie Mellon University, Pittsburgh, PA
Venue:
New developments in parsing technology
Year:
2004

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Abstract

This chapter 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.