A Viterbi-based morphological analysis for speech and natural language integration

This paper presents a statistical/symbolic hybrid morphological analysis, called V-morph, for large scale speech and natural language integration for Korean. In the V-morph approach, statistical Viterbi-based lexical decoding and symbolic morphological modeling are integrated together on top of connectionist phoneme recognition engine. Linguistic characteristics of Korean are appropriately considered in this speech and language modeling. Unlike word-based speech and language integration for most of the Indo-European language researches, we developed a morpheme-graph as a speech and language integration model for agglutinative languages. Preliminary experiments on morpheme spotting and sentence recognition based on connectionist phoneme recognition results verify that the V-morph and morpheme-graph are viable for complex integrated speech and natural language processing, and the approaches can be extended to other morphologically-complex agglutinative languages such as Japanese.