Tomohiro Ohno


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Construction of Responsive Utterance Corpus for Attentive Listening Response Production
Koichiro Ito | Masaki Murata | Tomohiro Ohno | Shigeki Matsubara
Proceedings of the Thirteenth Language Resources and Evaluation Conference

In Japan, the number of single-person households, particularly among the elderly, is increasing. Consequently, opportunities for people to narrate are being reduced. To address this issue, conversational agents, e.g., communication robots and smart speakers, are expected to play the role of the listener. To realize these agents, this paper describes the collection of conversational responses by listeners that demonstrate attentive listening attitudes toward narrative speakers, and a method to annotate existing narrative speech with responsive utterances is proposed. To summarize, 148,962 responsive utterances by 11 listeners were collected in a narrative corpus comprising 13,234 utterance units. The collected responsive utterances were analyzed in terms of response frequency, diversity, coverage, and naturalness. These results demonstrated that diverse and natural responsive utterances were collected by the proposed method in an efficient and comprehensive manner. To demonstrate the practical use of the collected responsive utterances, an experiment was conducted, in which response generation timings were detected in narratives.


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Relation between Degree of Empathy for Narrative Speech and Type of Responsive Utterance in Attentive Listening
Koichiro Ito | Masaki Murata | Tomohiro Ohno | Shigeki Matsubara
Proceedings of the Twelfth Language Resources and Evaluation Conference

Nowadays, spoken dialogue agents such as communication robots and smart speakers listen to narratives of humans. In order for such an agent to be recognized as a listener of narratives and convey the attitude of attentive listening, it is necessary to generate responsive utterances. Moreover, responsive utterances can express empathy to narratives and showing an appropriate degree of empathy to narratives is significant for enhancing speaker’s motivation. The degree of empathy shown by responsive utterances is thought to depend on their type. However, the relation between responsive utterances and degrees of the empathy has not been explored yet. This paper describes the classification of responsive utterances based on the degree of empathy in order to explain that relation. In this research, responsive utterances are classified into five levels based on the effect of utterances and literature on attentive listening. Quantitative evaluations using 37,995 responsive utterances showed the appropriateness of the proposed classification.


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Japanese Word Reordering Executed Concurrently with Dependency Parsing and Its Evaluation
Tomohiro Ohno | Kazushi Yoshida | Yoshihide Kato | Shigeki Matsubara
Proceedings of the 15th European Workshop on Natural Language Generation (ENLG)


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Japanese Word Reordering Integrated with Dependency Parsing
Kazushi Yoshida | Tomohiro Ohno | Yoshihide Kato | Shigeki Matsubara
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers


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Dependency Structure for Incremental Parsing of Japanese and Its Application
Tomohiro Ohno | Shigeki Matsubara
Proceedings of the 13th International Conference on Parsing Technologies (IWPT 2013)


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Coherent Back-Channel Feedback Tagging of In-Car Spoken Dialogue Corpus
Yuki Kamiya | Tomohiro Ohno | Shigeki Matsubara
Proceedings of the SIGDIAL 2010 Conference

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Automatic Comma Insertion for Japanese Text Generation
Masaki Murata | Tomohiro Ohno | Shigeki Matsubara
Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing

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Construction of Back-Channel Utterance Corpus for Responsive Spoken Dialogue System Development
Yuki Kamiya | Tomohiro Ohno | Shigeki Matsubara | Hideki Kashioka
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

In spoken dialogues, if a spoken dialogue system does not respond at all during user’s utterances, the user might feel uneasy because the user does not know whether or not the system has recognized the utterances. In particular, back-channel utterances, which the system outputs as voices such as “yeah” and “uh huh” in English have important roles for a driver in in-car speech dialogues because the driver does not look owards a listener while driving. This paper describes construction of a back-channel utterance corpus and its analysis to develop the system which can output back-channel utterances at the proper timing in the responsive in-car speech dialogue. First, we constructed the back-channel utterance corpus by integrating the back-channel utterances that four subjects provided for the driver’s utterances in 60 dialogues in the CIAIR in-car speech dialogue corpus. Next, we analyzed the corpus and revealed the relation between back-channel utterance timings and information on bunsetsu, clause, pause and rate of speech. Based on the analysis, we examined the possibility of detecting back-channel utterance timings by machine learning technique. As the result of the experiment, we confirmed that our technique achieved as same detection capability as a human.

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Construction of Chunk-Aligned Bilingual Lecture Corpus for Simultaneous Machine Translation
Masaki Murata | Tomohiro Ohno | Shigeki Matsubara | Yasuyoshi Inagaki
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

With the development of speech and language processing, speech translation systems have been developed. These studies target spoken dialogues, and employ consecutive interpretation, which uses a sentence as the translation unit. On the other hand, there exist a few researches about simultaneous interpreting, and recently, the language resources for promoting simultaneous interpreting research, such as the publication of an analytical large-scale corpus, has been prepared. For the future, it is necessary to make the corpora more practical toward realization of a simultaneous interpreting system. In this paper, we describe the construction of a bilingual corpus which can be used for simultaneous lecture interpreting research. Simultaneous lecture interpreting systems are required to recognize translation units in the middle of a sentence, and generate its translation at the proper timing. We constructed the bilingual lecture corpus by the following steps. First, we segmented sentences in the lecture data into semantically meaningful units for the simultaneous interpreting. And then, we assigned the translations to these units from the viewpoint of the simultaneous interpreting. In addition, we investigated the possibility of automatically detecting the simultaneous interpreting timing from our corpus.


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Linefeed Insertion into Japanese Spoken Monologue for Captioning
Tomohiro Ohno | Masaki Murata | Shigeki Matsubara
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP


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Dependency Parsing of Japanese Spoken Monologue Based on Clause Boundaries
Tomohiro Ohno | Shigeki Matsubara | Hideki Kashioka | Takehiko Maruyama | Yasuyoshi Inagaki
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

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A Syntactically Annotated Corpus of Japanese Spoken Monologue
Tomohiro Ohno | Shigeki Matsubara | Hideki Kashioka | Naoto Kato | Yasuyoshi Inagaki
Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)

Recently, monologue data such as lecture and commentary by professionals have been considered as valuable intellectual resources, and have been gathering attention. On the other hand, in order to use these monologue data effectively and efficiently, it is necessary for the monologue data not only just to be accumulated but also to be structured. This paper describes the construction of a Japanese spoken monologue corpus in which dependency structure is given to each utterance. Spontaneous monologue includes a lot of very long sentences composed of two or more clauses. In these sentences, there may exist the subject or the adverb common to multi-clauses, and it may be considered that the subject or adverb depend on multi-predicates. In order to give the dependency information in a real fashion, our research allows that a bunsetsu depends on multiple bunsetsus.