Dmai, Inc.

Changsong Liu

Rui Fang

The present teaching relates to method, system, medium, and implementations for enabling communication with a user. Information representing surrounding of a user to be engaged in a new dialogue is received via the communication platform, wherein the information is acquired from a scene in which the user is present and captures characteristics of the user and the scene. Relevant features are extracted from the information. A state of the user is estimated based on the relevant features, and a dialogue context surrounding the scene is determined based on the relevant features. A topic for the new dialogue is determined based on the user, and a feedback is generated to initiate the new dialogue with the user based on the topic, the state of the user, and the dialogue context.

System and method for intelligent initiation of a man-machine dialogue based on multi-modal sensory inputs

The present teaching relates to method, system, medium, and implementations for user machine dialogue. An instruction is received by an agent device for rendering a communication directed to a user involved in a dialogue in a dialogue scene and is used to render the communication. A first representation of a mindset of the agent is updated accordingly after the rendering. Input data are received in one or more media types capturing a response from the user and information surrounding the dialogue scene and a second representation of a mindset of the user is updated based on the response from the user and the information surrounding of the dialogue scene. A next communication to the user is then determined based on the first representation of the mindset of the agent and the second representation of the mindset of the user.

System and method for dialogue management

The present teaching relates to method, system, medium, and implementations for user machine dialogue. Historic dialogue data related to past dialogues are accessed and used to learn, via machine learning, expected utilities. During a dialogue involving a user and a machine agent, a representation of a shared mindset between the user and the agent is obtained to characterize the current state of the dialogue, which is then used to update the expected utilities. Continuous expected utility functions are then generated based on the updated expected utilities, wherein the continuous expected utility functions are to be used in determining how to conduct a dialogue with a user.

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Los Angeles, CA, United States of America

Changsong Liu