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  1. A500 情報学部/情報学研究科・情報文化学部・情報科学研究科
  2. A500e 会議資料
  3. 国際会議

SPIRAL CONSTRUCTION OF SYNTACTICALLY ANNOTATED SPOKEN LANGUAGE CORPUS

http://hdl.handle.net/2237/15085
b17934ff-b994-45b9-87ae-329db01d7aa7
名前 / ファイル ライセンス アクション
NLPKE2003_ohno.pdf NLPKE2003_ohno.pdf (269.5 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2011-07-20
タイトル
タイトル SPIRAL CONSTRUCTION OF SYNTACTICALLY ANNOTATED SPOKEN LANGUAGE CORPUS
著者 Ohno, Tomohiro

× Ohno, Tomohiro

WEKO 41636

Ohno, Tomohiro

Search repository
Matsubara, Shigeki

× Matsubara, Shigeki

WEKO 41637

Matsubara, Shigeki

Search repository
Kawaguchi, Nobuo

× Kawaguchi, Nobuo

WEKO 41638

Kawaguchi, Nobuo

Search repository
Inagaki, Yasuyoshi

× Inagaki, Yasuyoshi

WEKO 41639

Inagaki, Yasuyoshi

Search repository
権利
権利情報 (C) 2003 IEEE. Reprinted, with permission, from [Ohno, Tomohiro; Matsubara, Shigeki; Kawaguchi, Nobuo; Inagaki, Yasuyoshi, SPIRAL CONSTRUCTION OF SYNTACTICALLY ANNOTATED SPOKEN LANGUAGE CORPUS, proceedings : International Conference on Natural Language Processing and Knowledge Engineering in Beijing China on October 26-29. 2003].
キーワード
主題Scheme Other
主題 Stochastic parsing
キーワード
主題Scheme Other
主題 Dependency parsing
キーワード
主題Scheme Other
主題 Language database
キーワード
主題Scheme Other
主題 Spoken dialogue corpus
抄録
内容記述 Spontaneous speech includes a broad range of linguistic phenomena characteristic of spoken language, and therefore a statistical approach would be effective for robust parsing of spoken language. Though a largescale syntactically annotated corpus is required for the stochastic parsing, its construction requires a lot of human resources. This paper proposes a method of efficiently constructing a spoken language corpus for which the dependency analysis is provided. This method uses an existing spoken language corpus. A stochastic dependency parse is employed to tag spoken language sentences with the dependency structures, and the results are corrected manually. The tagged corpus is constructed in a spiral fashion where in the corrected data is utilized as the statistical information for automatic parsing of other data. Taking this spiral approach reduces the parsing errors, also allowing us to reduce the correction cost. An experiment using 10,995 Japanese utterances shows the spiral approach to be effective for efficient corpus construction.
内容記述タイプ Abstract
出版者
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
ISBN
関連識別子
識別子タイプ ISBN
関連識別子 0-7803-7902-0
書誌情報 NLP-KE2003 : proceedings : International Conference on Natural Language Processing and Knowledge Engineering in Beijing China

p. 477-483, 発行日 2003-10-26
著者版フラグ
値 author
URI
識別子 http://dx.doi.org/10.1109/NLPKE.2003.1275953
識別子タイプ DOI
URI
識別子 http://hdl.handle.net/2237/15085
識別子タイプ HDL
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