Name
Abstract | ||
|---|---|---|
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 novel 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. Experimental results reveal that the parsing accuracy reached 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. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1093/ietisy/e88-d.3.545 | IEICE Transactions |
Keywords | DocType | Volume |
written language,parsing accuracy,stochastic information,novel method,ill-formed phenomenon,location information,robust dependency parsing,dialogue sentence,grammatically ill-formed linguistic phenomenon,spontaneous japanese spoken language,distance information,language corpus,dependency parsing | Journal | E88-D |
Issue | ISSN | Citations |
3 | 1745-1361 | 5 |
PageRank | References | Authors |
0.60 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tomohiro Ohno | 1 | 31 | 10.06 |
| Shigeki Matsubara | 2 | 179 | 43.41 |
| Nobuo Kawaguchi | 3 | 313 | 64.23 |
| Yasuyoshi Inagaki | 4 | 243 | 44.27 |