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Factor Analysis of Utterances in Japanese Fiction-Writing Based on BCCWJ Speaker Information Corpus

机译:基于BCCWJ演讲者信息语料库的日语小说写作话语因素分析

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摘要

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 frequendy 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.
机译:为了分析日本小说中话语的特征,将几个属性(例如,说话者,听者,说话者与听者之间的关系以及说话者的性别)添加到随机抽取的日本小说语料库中。总共准备了887个数据集,带有5632个带注释的语音。基于带有属性的话语语料库,定量提取话语风格特征。卡方检验用于质点和助动词,以提取反映说话者和听者的性别以及他们之间的关系的发声特征。结果表明,男性人物中祈使词的使用率高于女性人物,后者使用了更多的动词,礼貌助剂被更多地用于“同事”和“上级权威”。另外,说话者和听者之间的亲密关系之间的发声也不同。此外,对BCCWJ演讲者信息语料库中的7576个数据集进行的重复因子分析揭示了十种典型的发声风格(中立,坦率,方言,礼貌,女性,粗俗,陈旧,疑问句,认可和花花公子)。因子得分表明了各种发声风格与说话人基本属性之间的关系。因此,这项研究的结果可用于说话人识别任务,自动语音生成任务以及对故事和角色的科学解释。

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  • 来源
    《Advances in human-computer interaction》 |2018年第2018期|5056268.1-5056268.9|共9页
  • 作者

    Hajime Murai;

  • 作者单位

    Department of Complex and Intelligent Systems, Future University Hakodate, Hakodate 041-8655, Japan;

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