@article{oai:ipsj.ixsq.nii.ac.jp:00226932,
 author = {松原, 真弓 and 麻場, 直喜 and 内藤, 昭一 and 川村, 晋太郎 and 井口, 慎也 and 能勢, 将樹 and 岡崎, 直観 and Mayumi, Matsubara and Naoki, Asaba and Shoichi, Naito and Shintaro, Kawamura and Shinya, Iguchi and Masaki, Nose and Naoki, Okazaki},
 issue = {3},
 journal = {情報処理学会論文誌デジタルプラクティス（DP）},
 month = {Jul},
 note = {深層学習をはじめとするAI技術の発展により，タスク指向対話システムを業務に活用するシーンが増えている．システムとユーザがより協調して業務を推進するには，ユーザが過去に話した内容を踏まえてタスクを遂行する必要がある．そこで今回，過去にユーザから報告を受けた事案の進捗を聞く対話システムを題材に，ユーザの使用頻度が高い言葉に基づいてユーザの報告内容を表現する「見出し生成モデル」を使ってシステムが獲得したい事案を端的かつユーザに合わせた形で表現するシステムを提案する．本研究では，過去の履歴データから比較的簡単なタスクとなるデータに絞ったうえでモデルを開発し，ユーザの特徴に合わせた表現が可能な，Rouge値0.7以上の精度となるモデルを構築した．生成モデルの出力を使った問いかけが，システムから送付されるメッセージとして違和感がないか，過去事案を思い出すのに役立つか，ユーザ評価した結果，4名中1名以上が肯定した問いかけは多かったが，メッセージとして不適切なものもあり，フィルタ等の処理など改善が必要であることが分かった．, In recent years, the development of AI technology such as deep learning has brought more demand to utilize task-oriented dialogue systems in business. In order to get more rational cooperation between the system and users, the system should take their past conversation into account during the task operations. From this point of view, we propose an approach to provide the users with appropriate information consisting of simple and customized phrases by exploiting a headline generation model. The headline generation model rephrases the input text from a user as a phrase based on higher frequently used words by referring to the past dialogue. In this study, we apply the headline generation model to our dialog system which asks our in-house sales staff about the progress of their past-reported items. Since we have selected the data so that the model can avoid complex tasks at this stage of the study, the model performs keeping ROUGE score above 0.7 where the generated phrases can be properly characterized by the users. As a result of the subjective evaluations by the users in terms of unnaturalness of the output messages and effectiveness as a reminder of their tasks, we obtained generally positive feedback. On the other hand, we also found that the proposed system still needs some improvement such as adding filtering process to reduce inappropriate outputs.},
 pages = {98--106},
 title = {タスク指向対話システムにおけるユーザの特徴を考慮した話題導入},
 volume = {4},
 year = {2023}
}