Abstract: A system for emotionally enhancing dialogue includes a computing platform having processing hardware and a system memory storing a software code including a predictive model. The processing hardware is configured to execute the software code to receive dialogue data identifying an utterance for use by a digital character in a conversation, analyze, using the dialogue data, an emotionality of the utterance at multiple structural levels of the utterance, and supplement the utterance with one or more emotional attributions, using the predictive model and the emotionality of the utterance at the multiple structural levels, to provide one or more candidate emotionally enhanced utterance(s).

Abstract: A system providing a multi-persona social agent includes a computing platform having a hardware processor, a system memory storing a software code, and multiple neural network (NN) based predictive models accessible by the software code. The hardware processor executes the software code to receive input data corresponding to an interaction with a user, determine a generic expression for use in the interaction, and identify one of the character personas as a persona to be assumed by the multi-persona social agent. The software code also generates, using the generic expression and one of the NN based predictive models corresponding to the persona to be assumed by the multi-persona social agent, a sentiment driven personified response for the interaction with the user based on a vocabulary, phrases, and one or more syntax rules idiosyncratic to the persona to be assumed, and renders the sentiment driven personified response using the multi-persona social agent.

Abstract: A system includes a computing platform having one or more processor(s) configured to receive input data corresponding to an interaction with a user, to determine a character archetype, an intent, and a sentiment of the user, to generate, using the input data and the character archetype, an output data that includes a token describing a payload, and to identify, using the token, a database corresponding to the payload. The processor(s) are further configured to obtain, by searching the database based on the character archetype, the intent, and the sentiment of the user, the payload from the database, to transform, using the character archetype and the intent and the sentiment of the user, the output data and the payload to a response to the interaction, and to render the response using a social agent that assumes the character archetype.

Abstract: A system providing a multi-persona social agent includes a computing platform having a hardware processor, a system memory storing a software code, and multiple neural network (NN) based predictive models accessible by the software code. The hardware processor executes the software code to receive input data corresponding to an interaction with a user, determine a generic expression for use in the interaction, and identify one of the character personas as a persona to be assumed by the multi-persona social agent. The software code also generates, using the generic expression and one of the NN based predictive models corresponding to the persona to be assumed by the multi-persona social agent, a sentiment driven personified response for the interaction with the user based on a vocabulary, phrases, and one or more syntax rules idiosyncratic to the persona to be assumed, and renders the sentiment driven personified response using the multi-persona social agent.