Towards personalized persuasive dialogue generation for adversarial task oriented dialogue setting. (1st March 2023)

• Record Type: Journal Article
• Authors: Tiwari, Abhisek; Khandwe, Abhijeet; Saha, Sriparna; Ramnani, Roshni; Maitra, Anutosh; Sengupta, Shubhashis
• Is Part Of: Expert systems with applications. Volume 213:Part A(2023)
• Publication Date: 2023-03-01
• Subjects: Conversational agents -- Goal unavailability -- Personalization -- Persuasion -- Discourse -- E-commerce; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2022.118775
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: In recent years, task-oriented virtual assistants have gained huge popularity and demand in both research and industry communities. The primary aim of a task-oriented dialogue agent is to assist end-users in accomplishing a task successfully and satisfactorily. Existing virtual agents have acquired proficiency in assisting users in solving simple tasks such as restaurant bookings. However, they operate under the deterministic presumption that end-users will have a servable task objective, which makes them inadequate under adversarial situations such as goal unavailability. On the other hand, human agents accomplish users' tasks even in many goal unavailability scenarios by persuading them towards a similar goal to the user's proposed task. Motivated by the limitation, the current work proposes and builds a novel transformer-based context-aware personalized persuasive virtual assistant (CoPersUasive VA), which also serves end-users in task unavailability situations. The proposed CoPersUasive VA recognizes goal conflicts through user sentiment and identifies an appropriate persuasion strategy using ongoing dialogue context and user personality. Depending on users' proposed goals, it finds a similar servable goal and persuades them with the identified persuasion strategy. The obtained experimental results and detailed post-analysis firmly establish that the proposed model effectively enhances the capability of task-oriented virtual assistants to deal with the task failures caused by goal unavailability. The obtained findings also suggest the crucial role of dialogue context in identifying an appropriate and appealing persuasion strategy. The proposed CoPersUasive model could easily be adapted to any other domain by fine-tuning the model on an underlying task. Furthermore, we developed a personalized persuasive multi-intent conversational dialogue corpus annotated with intent, slot, sentiment, and dialogue act for electronic domain. 2 Highlights: Existing dialogue agents fail to cope with goal unavailability situations. In real life, agents find similar goals and persuade users. Persuasion is very much subjective and context-dependent. Neural method for developing a cooperative and personalized persuasive assistant. Context-aware, Personalized Persuasive Dialogue Corpus for e-commerce domain.