Glr* : a Robust Parser for Spontaneously Spoken Language

This paper describes GLR*, a parsing system based on Tomita's Generalized LR parsing algorithm, that was designed to be robust to two particular types of extra-grammaticality: noise in the input, and limited grammar coverage. GLR* attempts to overcome these forms of extra-grammaticality by ignoring the unparsable words and fragments and conducting a search for the maximal subset of the original input that is covered by the grammar. The parser is coupled with a beam search heuristic, that limits the combinations of skipped words considered by the parser, and ensures that the parser will operate within feasible time and space bounds. The developed parsing system includes several tools designed to address the diiculties of parsing spontaneous speech: a statistical disambiguation module, an integrated heuristic for evaluating and ranking the parses produced by the parser, and a parse quality heuristic, that allows the parser to self-judge the quality of the parse chosen as best. To evaluate its suitability to parsing spontaneous speech, the GLR* parser was integrated into the JANUS speech translation system. Our evaluations on both transcribed and speech recognized input have indicated that the version of the system that uses GLR* produces about 30% more acceptable translations, than a corresponding version that uses the original non-robust GLR parser.