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Machine Learning Summit: Emotional Neural Style Transfer: Expressing Character AI Emotion through Paintings

Edgar Handy  (Machine Learning Engineer, SQUARE ENIX CO., LTD)

Pass Type: All Access Pass, Summits Pass - Get your pass now!

Topic: Programming

Format: Session

Vault Recording: TBD

Audience Level: No

Recently machine learning has been applied mostly for asset creations. We take a new step on applying machine learning in game AI to transform the way a character AI expresses its emotion, which generally has been limited to facial expression, body gesture, and vocal intonation. In particular, we adopted neural style transfer that visualizes the AI’s feeling. The session covers how the emotion controls the style transfer, the in-depth explanation of the style transfer model, and how it is implemented in the game. The character AI documents what it sees along its journey in the form of painting and uses style transfer to visualize its feeling to the player, allowing a new kind of player-AI interaction in the game. The character can also use style blending and region masking to focus on a particular aspect of the paintings according to its interests.


The attendees are presented a technical detail of an experiment to extend emotional expression of character AI. The attendees will gain understanding how the combination of emotional component and style transfer works, the detail of style transfer model, and its implementation.

Intended Audience

The session is intended for AI/Gameplay programmers and Game Designers that are interested in the application and implementation of neural style transfer in game AI and human-AI interaction. Basic understanding of machine learning is useful.