Disney Enterprises, Inc.

Komath Naveen Kumar

James R Kennedy

Douglas A Fidaleo

Raymond J Scanlon

Salvator D Lombardo

Dawson McLeod Dill

John Wiseman

Robert P Michel

Ashley N Girdich

Prashanth Gurunath Shivakumar

A system for performing context-based management of social agent interactions includes processing hardware and a memory storing a software code. The processing hardware executes the software code to detect the presence of an interaction partner, identify a present state of an interaction with the interaction partner, and to determine, based on the present state, a first score for each of multiple interactive expressions for use in initiating or continuing the interaction. The processing hardware further executes the software code to predict a state change of the interaction based on each of the interactive expressions to provide multiple predicted state changes corresponding respectively to the multiple interactive expressions, to determine, using the predicted state changes, a second score for each of the interactive expressions, and to select, using the first scores and the second scores, at least one of the interactive expressions to initiate or continue the interaction.

Context-based social agent interaction

A system for monitoring and improving social agent interaction quality includes a computing platform having processing hardware and a system memory storing a software code. The processing hardware is configured to execute the software code to receive, from a social agent, interaction data describing an interaction of the social agent with a user, and to perform an assessment of the interaction, using the interaction data, as one of successful or including a flaw. When the assessment indicates that the interaction includes the flaw, the processing hardware is further configured to execute the software code to identify an interaction strategy for correcting the flaw, and to deliver, to the social agent, one or both of the assessment and the interaction strategy to correct the flaw in the interaction.

Automated social agent interaction quality monitoring and improvement

A system for incremental natural language understanding includes a media module, a memory storing a software code, and a hardware processor communicatively coupled to the media module. The hardware processor is configured to execute the software code to receive an audio stream including a first utterance, and generate a first and second incremental speech recognition outputs based on first and second portions of the first utterance. In addition, the hardware processor is configured to execute the software code to determine, prior to generating the second incremental speech recognition output, a first intent of the first utterance based on the first incremental speech recognition output. The hardware processor is further configured to execute the software code to retrieve a first resource based on the determined first intent, and incorporate the first resource in the media content to be played by the media module.

Systems and methods for incremental natural language understanding

An audio processing system for generating audio including emotionally expressive synthesized content includes a computing platform having a hardware processor and a memory storing a software code including a trained neural network. The hardware processor is configured to execute the software code to receive an audio sequence template including one or more audio segment(s) and an audio gap, and to receive data describing one or more words for insertion into the audio gap. The hardware processor is configured to further execute the software code to use the trained neural network to generate an integrated audio sequence using the audio sequence template and the data, the integrated audio sequence including the one or more audio segment(s) and at least one synthesized word corresponding to the one or more words described by the data.

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Los Angeles, CA, United States of America

Komath Naveen Kumar