@article{oai:nagoya.repo.nii.ac.jp:00001299,
 author = {大野, 誠寛 and Ohno, Tomohiro and 松原, 茂樹 and Matsubara, Shigeki and 河口, 信夫 and Kawaguchi, Nobuo and Inagaki, Yasuyoshi},
 journal = {Proceedings of  the 8th International Conference on Spoken Language Processing (Interspeech-2004)},
 month = {Oct},
 note = {Spontaneously spoken Japanese includes a lot of grammatically ill-formed linguistic phenomena such as fillers, hesitations, inversions, and so on, which do not appear in written language. This paper proposes a method of robust dependency parsing using a large-scale spoken language corpus, and evaluates the availability and robustness of the method using spontaneously spoken dialogue sentences. By utilizing stochastic information about the appearance of ill-formed phenomena, the method can robustly parse spoken Japanese including fillers, inversions, or dependencies over utterance units. As a result of an experiment, the parsing accuracy provided 87.0%, and we confirmed that it is effective to utilize the location information of a bunsetsu, and the distance information between bunsetsus as stochastic information., Grant-in-Aids for Young Scientists of the Ministry of Education, Science, Sports and Culture, Japan;<br/>The Tatematsu Foundation},
 pages = {2173--2176},
 title = {Robust Dependency Parsing of Spontaneous Japanese Speech and Its Evaluation},
 year = {2004}
}