  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.
