Yuichi Ishimoto


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Design and Evaluation of the Corpus of Everyday Japanese Conversation
Hanae Koiso | Haruka Amatani | Yasuharu Den | Yuriko Iseki | Yuichi Ishimoto | Wakako Kashino | Yoshiko Kawabata | Ken’ya Nishikawa | Yayoi Tanaka | Yasuyuki Usuda | Yuka Watanabe
Proceedings of the Thirteenth Language Resources and Evaluation Conference

We have constructed the Corpus of Everyday Japanese Conversation (CEJC) and published it in March 2022. The CEJC is designed to contain various kinds of everyday conversations in a balanced manner to capture their diversity. The CEJC features not only audio but also video data to facilitate precise understanding of the mechanism of real-life social behavior. The publication of a large-scale corpus of everyday conversations that includes video data is a new approach. The CEJC contains 200 hours of speech, 577 conversations, about 2.4 million words, and a total of 1675 conversants. In this paper, we present an overview of the corpus, including the recording method and devices, structure of the corpus, formats of video and audio files, transcription, and annotations. We then report some results of the evaluation of the CEJC in terms of conversant and conversation attributes. We show that the CEJC includes a good balance of adult conversants in terms of gender and age, as well as a variety of conversations in terms of conversation forms, places, activities, and numbers of conversants.


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A Conversation-Analytic Annotation of Turn-Taking Behavior in Japanese Multi-Party Conversation and its Preliminary Analysis
Mika Enomoto | Yasuharu Den | Yuichi Ishimoto
Proceedings of the Twelfth Language Resources and Evaluation Conference

In this study, we propose a conversation-analytic annotation scheme for turn-taking behavior in multi-party conversations. The annotation scheme is motivated by a proposal of a proper model of turn-taking incorporating various ideas developed in the literature of conversation analysis. Our annotation consists of two sets of tags: the beginning and the ending type of the utterance. Focusing on the ending-type tags, in some cases combined with the beginning-type tags, we emphasize the importance of the distinction among four selection types: i) selecting other participant as next speaker, ii) not selecting next speaker but followed by a switch of the speakership, iii) not selecting next speaker and followed by a continuation of the speakership, and iv)being inside a multi-unit turn. Based on the annotation of Japanese multi-party conversations, we analyze how syntactic and prosodic features of utterances vary across the four selection types. The results show that the above four-way distinction is essential to account for the distributions of the syntactic and prosodic features, suggesting the insufficiency of previous turn-taking models that do not consider the distinction between i) and ii) or between ii) or iii).

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KOTONOHA: A Corpus Concordance System for Skewer-Searching NINJAL Corpora
Teruaki Oka | Yuichi Ishimoto | Yutaka Yagi | Takenori Nakamura | Masayuki Asahara | Kikuo Maekawa | Toshinobu Ogiso | Hanae Koiso | Kumiko Sakoda | Nobuko Kibe
Proceedings of the Twelfth Language Resources and Evaluation Conference

The National Institute for Japanese Language and Linguistics, Japan (NINJAL, Japan), has developed several types of corpora. For each corpus NINJAL provided an online search environment, ‘Chunagon’, which is a morphological-information-annotation-based concordance system made publicly available in 2011. NINJAL has now provided a skewer-search system ‘Kotonoha’ based on the ‘Chunagon’ systems. This system enables querying of multiple corpora by certain categories, such as register type and period.


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Extending Search System based on Interactive Visualization for Speech Corpora
Tomoko Ohsuga | Yuichi Ishimoto | Tomoko Kajiyama | Shunsuke Kozawa | Kiyotaka Uchimoto | Shuichi Itahashi
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


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Towards Automatic Transformation between Different Transcription Conventions: Prediction of Intonation Markers from Linguistic and Acoustic Features
Yuichi Ishimoto | Tomoyuki Tsuchiya | Hanae Koiso | Yasuharu Den
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Because of the tremendous effort required for recording and transcription, large-scale spoken language corpora have been hardly developed in Japanese, with a notable exception of the Corpus of Spontaneous Japanese (CSJ). Various research groups have individually developed conversation corpora in Japanese, but these corpora are transcribed by different conventions and have few annotations in common, and some of them lack fundamental annotations, which are prerequisites for conversation research. To solve this situation by sharing existing conversation corpora that cover diverse styles and settings, we have tried to automatically transform a transcription made by one convention into that made by another convention. Using a conversation corpus transcribed in both the Conversation-Analysis-style (CA-style) and CSJ-style, we analyzed the correspondence between CA’s ‘intonation markers’ and CSJ’s ‘tone labels,’ and constructed a statistical model that converts tone labels into intonation markers with reference to linguistic and acoustic features of the speech. The result showed that there is considerable variance in intonation marking even between trained transcribers. The model predicted with 85% accuracy the presence of the intonation markers, and classified the types of the markers with 72% accuracy.