Phoneme-level speech and natural language intergration for agglutinative languages
<|reference_start|>Phoneme-level speech and natural language intergration for agglutinative languages: A new tightly coupled speech and natural language integration model is presented for a TDNN-based large vocabulary continuous speech recognition system. Unlike the popular n-best techniques developed for integrating mainly HMM-based speech and natural language systems in word level, which is obviously inadequate for the morphologically complex agglutinative languages, our model constructs a spoken language system based on the phoneme-level integration. The TDNN-CYK spoken language architecture is designed and implemented using the TDNN-based diphone recognition module integrated with the table-driven phonological/morphological co-analysis. Our integration model provides a seamless integration of speech and natural language for connectionist speech recognition systems especially for morphologically complex languages such as Korean. Our experiment results show that the speaker-dependent continuous Eojeol (word) recognition can be integrated with the morphological analysis with over 80\% morphological analysis success rate directly from the speech input for the middle-level vocabularies.<|reference_end|>
@article{kim1994phoneme-level,
    title={Phoneme-level speech and natural language intergration for agglutinative
  languages},
    author={Geunbae Lee Jong-Hyeok Lee Kyunghee Kim (Department of Computer
  Science & Engineering and Postech Information Research Laboratory Pohang
  University of Science & Technology, Korea)},
    journal={arXiv preprint arXiv:cmp-lg/9411013},
    year={1994},
    archivePrefix={arXiv},
    eprint={cmp-lg/9411013},
    primaryClass={cmp-lg cs.CL}
}