Impersonation: Modeling Persona in Smart Responses to Email
Rajeev Gupta, Ranganath Kondapally, Chakrapani Ravi Kiran

TL;DR
This paper introduces a personalized email response suggestion system that models user persona and context to generate responses that mimic individual styles, enhancing productivity and personalization.
Contribution
It presents a novel approach to modeling user persona and context for personalized email response generation, integrating multimodal responses.
Findings
Effective personalization of email responses achieved
Model captures user style and context accurately
Responses include text and audio modes
Abstract
In this paper, we present design, implementation, and effectiveness of generating personalized suggestions for email replies. To personalize email responses based on users style and personality, we model the users persona based on her past responses to emails. This model is added to the language-based model created across users using past responses of the all user emails. A users model captures the typical responses of the user given a particular context. The context includes the email received, recipient of the email, and other external signals such as calendar activities, preferences, etc. The context along with users personality (e.g., extrovert, formal, reserved, etc.) is used to suggest responses. These responses can be a mixture of multiple modes: email replies (textual), audio clips, etc. This helps in making responses mimic the user as much as possible and helps the user to be…
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Taxonomy
TopicsPersona Design and Applications · Innovative Human-Technology Interaction · AI in Service Interactions
