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Abstract : |
One of the major problems one is faced with when decomposing words into their constituent parts is ambiguity: the gen-eration of multiple analyses for one input word, many of which are implausible. In order to deal with ambiguity, the MOR-phological PArser MORPA is provided with a probabilistic context-free grammar (PCFG), i.e. it combines a "conventional" context-free morphological grammar to fil-ter out ungrammatical segmentations with a probability-based scoring function which determines the likelihood of each success-ful parse. Consequently, remaining analy-ses can be ordered along a scale of plausi-bility. Test performance data will show that a PCFG yields good results in morphologi-cal parsing. MORPA is a fully implemented parser developed for use in a text-to-speech conversion system. 1, |
