Impersonation: Modeling Persona in Smart Responses to Email
This addresses the need for more efficient and personalized email communication for users, though it appears incremental as it builds on existing language models with added persona modeling.
The paper tackles the problem of generating personalized email reply suggestions by modeling a user's persona from past responses, incorporating context and personality traits to mimic the user's style, aiming to enhance productivity while maintaining personalization.
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 more productive while retaining her mark in the responses.