Integrated speech and morphological processing in a connectionist continuous speech understanding for Korean
<|reference_start|>Integrated speech and morphological processing in a connectionist continuous speech understanding for Korean: A new tightly coupled speech and natural language integration model is presented for a TDNN-based continuous possibly large vocabulary speech recognition system for Korean. Unlike popular n-best techniques developed for integrating mainly HMM-based speech recognition and natural language processing in a {\em word level}, which is obviously inadequate for morphologically complex agglutinative languages, our model constructs a spoken language system based on a {\em morpheme-level} speech and language integration. With this integration scheme, the spoken Korean processing engine (SKOPE) is designed and implemented using a TDNN-based diphone recognition module integrated with a Viterbi-based lexical decoding and symbolic phonological/morphological co-analysis. Our experiment results show that the speaker-dependent continuous {\em eojeol} (Korean word) recognition and integrated morphological analysis can be achieved with over 80.6% success rate directly from speech inputs for the middle-level vocabularies.<|reference_end|>
@article{lee1996integrated,
    title={Integrated speech and morphological processing in a connectionist
  continuous speech understanding for Korean},
    author={Geunbae Lee, Jong-Hyeok Lee (Department of Computer Science and
  Engineering Pohang University of Science and Technology)},
    journal={arXiv preprint arXiv:cmp-lg/9603005},
    year={1996},
    archivePrefix={arXiv},
    eprint={cmp-lg/9603005},
    primaryClass={cmp-lg cs.CL}
}