Factor Analysis of Utterances in Japanese Fiction-Writing Based on BCCWJ Speaker Information Corpus
Factor Analysis of Utterances in Japanese Fiction-Writing Based on BCCWJ Speaker Information Corpus
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基于BCCWJ说话人信息语料库的日本小说写作话语因素分析
DOI：
10.1155/2018/5056268
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
H. Murai
中科院分区：
文献类型：
--
作者：
H. Murai
为了分析日语小说中的话语特征，在随机抽取的日语小说语料库中加入了几个属性(如说话人、听话人、说话人和听话人的关系以及说话人的性别)。共准备了887个数据集和5632个带注释的话语。基于带属性标注的话语语料库，定量提取了话语风格特征。对助词和助动词进行卡方检验，提取反映说话人和听话人性别及其关系的话语特征。结果表明，男性角色使用祈使词的频率高于女性角色，男性角色使用助词的频率高于女性角色，礼貌助词更多地用于同事和上级权威。此外，在说话人和听话人之间的亲密关系中，话语也各不相同。此外，对BCCWJ说话人信息语料库中的7576个语料进行了重复因素分析，发现了十种典型的话语风格(中性、坦率、方言、礼貌、女性、粗鲁、老年、疑问、赞许和花哨)。因子分表明了不同发音风格与说话人基本属性之间的关系。因此，这项研究的结果将可用于说话人识别任务、自动语音生成任务以及对故事和人物的科学解释。
To analyse the characteristics of utterances in Japanese novels, several attributes (e.g., the speaker, listener, relationship between the speaker and listener, and gender of the speaker) were added to a randomly extracted Japanese novel corpus. A total of 887 data sets, with 5632 annotated utterances, were prepared. Based on the attribute annotated utterance corpus, the characteristics of utterance styles were extracted quantitatively. A chi-square test was used for particles and auxiliary verbs to extract utterance characteristics which reflected the genders of and relationships between the speakers and listeners. Results revealed that the use of imperative words was higher among male characters than their female counterparts, who used more particle verbs, and that auxiliaries of politeness were used more frequently for ‘coworkers’ and ‘superior authorities’. In addition, utterances varied between close and intimate relationships between the speaker and listener. Moreover, repeated factor analyses for 7576 data sets in BCCWJ speaker information corpus revealed ten typical utterance styles (neutral, frank, dialect, polite, feminine, crude, aged, interrogative, approval, and dandy). The factor scores indicated relationships between various utterance styles and fundamental attributes of speakers. Thus, results of this study would be utilisable in speaker identification tasks, automatic speech generation tasks, and scientific interpretation of stories and characters.
DOI：
10.1002/asi.v60:3
发表时间：
2009-03
影响因子：
3.5
作者：
N. Shibata;Y. Kajikawa;Y. Takeda;K. Matsushima
通讯作者：
N. Shibata;Y. Kajikawa;Y. Takeda;K. Matsushima