GLR parsing of word lattices using a beam search method

The process of understanding spoken language requires the efficient processing of ambiguities that arise by the nature of speech. This paper presents an approach that allows the efficient incremental integration of speech recognition and language understanding using Tomita´s generalized LR-parsing algorithm. For this purpose the GLR-lattice-parsing-algorithm is revised so that an agenda mechanism can be used to control the flow of computation of the parsing process. Subsequently the HMM-evaluations of the word models are combined with a stochastical language model to do a beam search similar to where chartparsers are used to do the job.