モンゴルの会話の技法

Fundamentals Review, 2015

This article sheds light on principles of human-human communication such as everyday conversation. Traditional views of communication generally have the following four principles in common: communication is (i) based on information transfer, (ii) the participants' intentions, (iii) co-presence among participants, and (iv) actions. These principles, however, actually often obfuscate various phenomena and distort their descriptions and explanations. This articles shows this concretely through an observation of modern spoken Japanese. Then, a more useful view of communication is elicited that captures communication as a part of participants' lives based on a consciousness that states, "My co-presence with others is mutually acknowledged by others."

博士論文 学術, 1991

2018

国立国語研究所 研究系 音声言語研究領域 非常勤研究員千葉大学大学院 博士課程／国立国語研究所 研究系 音声言語研究領域 非常勤研究員国立国語研究所 コーパス開発センター 非常勤研究員国立国語研究所 コーパス開発センター国立国語研究所 研究系 音声言語研究領域Adjunct Researcher, Spoken Language Division, Research Department, NINJALDoctoral Student, Chiba University / Adjunct Researcher, Spoken Language Division, Research Department, NINJALAdjunct Researcher, Center for Corpus Development, NINJALCenter for Corpus Development, NINJALSpoken Language Division, Research Department, NINJAL本稿は，平成28年度から構築を進めている『日本語日常会話コーパス』における転記の基準と作成手法について述べる。本コーパスには，日常場面で自然に生じるさまざまなタイプの会話200時間がバランス良く収録される予定である。日常会話には，極めてくだけた表現や，聞き取りづらい，あるいは把握しづらい表現が頻出する。こうした会話データを多人数により均質に書き起こすには，転記のための基準を明確に定める必要がある。また，200時間という大量の会話を限られた期間で書き起こすために，効率的に作業をするための工夫が必要になる。本プロジェクトでは，実際の会話データを対象に転記を行いながら，効率的に作業をするための工程を検討し，ツールの開発や転記基準の改訂を行ってきた。本稿では，このようにして策定した転記基準と，作業を効率的に進めるために整備した方法について紹介する。This paper describes the criteria and composition method of transcription for the Corpus of Everyday Japanese Conversation, which has been in construction since 2...

Transactions of the Japanese Society for Artificial Intelligence, 2016

There is a growing interest in conversation agents and robots which conduct attentive listening. However, the current systems always generate the same or limited forms of backchannels every time, giving a monotonous impression. This study investigates the generation of a variety of backchannel forms appropriate for the dialogue context, using the corpus of counseling dialogue. At first, we annotate all acceptable backchannel form categories considering the permissible variation in backchannels. Second, we analyze how the morphological form of backchannels relates to linguistic features of the preceding utterance such as the utterance boundary type and the linguistic complexity. Based on this analysis, we conduct machine learning to predict backchannel form from the linguistic and prosodic features of the preceding context. This model outperformed a baseline which always outputs the same form of backchannels and another baseline which randomly generates backchannels. Finally, subjective evaluations by human listeners show that the proposed method generates backchannels more naturally and gives a feeling of understanding and empathy.

Transactions of the Japanese Society for Artificial Intelligence

This paper focuses on developing a model for estimating communication skills of each participant in a group from multimodal (verbal and nonverbal) features. For this purpose, we use a multimodal group meeting corpus including audio signal data and head motion sensor data of participants observed in 30 group meeting sessions. The corpus also includes the communication skills of each participant, which is assessed by 21 external observers with the experience of human resource management. We extracted various kinds of features such as spoken utterances, acoustic features, speaking turns and the amount of head motion to estimate the communication skills. First, we created a regression model to infer the level of communication skills from these features using support vector regression to evaluate the estimation accuracy of the communication skills. Second, we created a binary (high or low) classification model using support vector machine. Experiment results show that the multimodal model achieved 0.62 in R 2 as the regression accuracy of overall skill, and also achieved 0.93 as the classification accuracy. This paper reports effective features in predicting the level of communication skill and shows that these features are also useful in characterizing the difference between the participants who have high level communication skills and those who do not.

1992

2008

2017

日本では「不思議のダンジョン」シリーズで名高いローグライクゲームは，マップや敵配置がランダムなこと，そのため臨機応変にアイテム等を使い分ける必要があることなどを特徴とする一人用ダンジョン探索ゲームの総称である．囲碁や将棋などよりは複雑で，StarcraftやCivilizationなどよりは単純なこのゲーム群は，短期的戦術と長期的スケジューリングの両方を要するなど，高度なゲームAIを研究するうえでの良い課題をいくつも持つ．本論文では，学術用プラットフォームを共有できるようにするために，ローグライクゲームの最低限の要素を持たせたゲームのルールを提案した．そのうえで，ルールベースのコンピュータプレイヤ，短期的な戦術行動を改善するためのモンテカルロ法プレイヤ，長期的な視点での行動が取れるようにするための教師あり学習を提案した．: Roguelike Game, known as "Mystery Dungeon" in Japan, is a genre of one-player role-playing video games. In roguelike games, the map is randomly created and the monsters are randomly located every play, then the player needs to select his strategy properly according to the given situation. Roguelike games are more complex than the game of Go or Chess, and less complex than Starcraft or Civilization. They are less complex, still they have several typical problems for sophisticated game AIs, for example both of short-time strategy and long-time scheduling are necessary and the balancing is important. In this paper, ...

2010

博士(Doctor)工学(Engineering)奈良先端科学技術大学院大学博第977号甲第977号博士(工学)奈良先端科学技術大学院大

2010

Transactions of the Japanese Society for Artificial Intelligence, 2007

This paper describes how to perform syntactic parsing and semantic analysis in a dialog system. The paper especially deals with how to disambiguate potentially ambiguous sentences using the contextual information. Although syntactic parsing and semantic analysis are often studied independently of each other, correct parsing of a sentence often requires the semantic information on the input and/or the contextual information prior to the input. Accordingly, we merge syntactic parsing with semantic analysis, which enables syntactic parsing taking advantage of the semantic content of an input and its context. One of the biggest problems of semantic analysis is how to interpret dependency structures. We employ a framework for semantic representations that circumvents the problem. Within the framework, the meaning of any predicate is converted into a semantic representation which only permits a single type of predicate: an identifying predicate "aru". The semantic representations are expressed as sets of "attribute-value" pairs, and those semantic representations are stored in the context information. Our system disambiguates syntactic/semantic ambiguities of inputs referring to the attribute-value pairs in the context information. We have experimentally confirmed the effectiveness of our approach; specifically, the experiment confirmed high accuracy of parsing and correctness of generated semantic representations.

Hiroshima Studies in Language and Language Education, 2005

Acoustical Science and Technology, 1998

Bulletin of the Graduate School of Engineering Hiroshima University, 2006

中国地区英語教育学会研究紀要 Casele Research Bulletin, 2004