AbstractThis paper describes GLR*, a parser that can parse any input sentence by ignoring unrecognizable parts of the sentence. In case the standard parsing procedure fails to parse an input sentence, the parser nondeterministically skips some word(s) in the sentence, and returns the parse with fewest skipped words. Therefore, the parser will return some parse(s) with any input sentence, unless no part of the sentence can be recognized at all. The problem can be defined in the following way: Given a context-free grammar G and a sentence S, find and parse S' – the largest subset of words of S, such that S' ∈ L(G). The algorithm described in this paper is a modification of the Generalized LR (Tomita) parsing algorithm [Tomita, 1986] . The parser accommodates the skipping of words by allowing shift operations to be performed from inactive state nodes of the Graph Structured Stack. A heuristic similar to beam search makes the algorithm computationally tractable. There have been several other approaches to the problem of robust parsing, most of which are special purpose algorithms [Carbonell and Hayes, 1984] , [Ward, 1991] and others. Because our approach is a modification to a standard context-free parsing algorithm, all the techniques and grammars developed for the standard parser can be applied as they are. Also, in case the input sentence is by itself grammatical, our parser behaves exactly as the standard GLR parser. The modified parser, GLR*, has been implemented and integrated with the latest version of the Generalized LR Parser/Compiler [Tomita et al , 1988], [Tomita, 1990]. We discuss an application of the GLR* parser to spontaneous speech understanding and present some preliminary tests on the utility of the GLR* parser in such settings.