Reinforcing personalized persuasion in task-oriented virtual sales assistant

Aritra Raut, Abhisek Tiwari, Subrata Das, Sriparna Saha, Anutosh Maitra, Roshni Ramnani and Shubhashis Sengupta

PLOS ONE, 2023, vol. 18, issue 1, 1-27

Abstract: Purpose: Existing task-oriented virtual agents can assist users with simple tasks like ticket booking, hotel reservations, etc. effectively and with high confidence. These virtual assistants, however, assume specific, predictable end-user behavior, such as predefined/servable objectives, which results in conversation failures in challenging situations, such as when goals are unavailable. Methodology: Inspired by the practice and its efficacy, we propose an end-to-end framework for task-oriented persuasive dialogue generation that combines pre-training and reinforcement learning for generating context-aware persuasive responses. We utilize four novel rewards to improve consistency and repetitiveness in generated responses. Additionally, a meta-learning strategy has also been utilized to make the model parameters better for domain adaptation. Furthermore, we also curate a personalized persuasive dialogue (PPD) corpus, which contains utterance-level intent, slot, sentiment, and persuasion strategy annotation. Findings: The obtained results and detailed analysis firmly establish the effectiveness of the proposed persuasive virtual assistant over traditional task-oriented virtual assistants. The proposed framework considerably increases the quality of dialogue generation in terms of consistency and repetitiveness. Additionally, our experiment with a few shot and zero-shot settings proves that our meta-learned model learns to quickly adopt new domains with a few or even zero no. of training epochs. It outperforms the non-meta-learning-based approaches keeping the base model constant. Originality: To the best of our knowledge, this is the first effort to improve a task-oriented virtual agent’s persuasiveness and domain adaptation.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0275750

DOI: 10.1371/journal.pone.0275750

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