Virtual Conversational Companion Synchronized Multimedia Outputs
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Solution Overview
Problem
Current natural language processing systems struggle to provide a seamless and engaging user experience through synchronized outputs of synthesized speech, images, and personified visual representations of virtual assistants, especially in dynamic contexts like storytelling.
Innovation Solution
A system that integrates automatic speech recognition, natural language understanding, and text-to-speech processing to generate synchronized outputs, including synthesized speech, images, and dynamic avatars, in response to user inputs, allowing for interactive storytelling and content delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language processing systems provide synchronized outputs of synthesized speech, images, and personified visual representations, then user engagement and interaction quality are improved, but system complexity increases
Solution Approach 1:
The patent combines multiple output modalities (synthesized speech, images, and personified visual representations) into a single integrated system that processes user inputs and generates synchronized multimedia responses. The system merges speech recognition, natural language understanding, text-to-speech processing, and visual generation components to create a cohesive virtual assistant experience.
Solution Approach 2:
The virtual assistant system performs multiple functions through a single platform, including speech recognition, natural language understanding, text generation, speech synthesis, and visual content creation. This multi-functional approach allows one system to handle diverse user interactions and deliver rich multimedia responses without requiring separate specialized systems.
2Ease of operation
If the system generates dynamic and context-aware responses, then interaction quality improves, but processing time increases
Solution Approach 1:
The system performs preliminary processing of user inputs through speech recognition and natural language understanding before generating responses. By pre-processing the input data and understanding the context beforehand, the system can more efficiently generate appropriate responses, reducing overall processing time while maintaining high interaction quality.
Solution Approach 2:
The system incorporates feedback mechanisms that allow it to learn from user interactions and adjust its processing accordingly. By analyzing user responses and interaction patterns, the system can optimize its processing efficiency and reduce response times while maintaining context-aware and dynamic interactions.
Data Source
AI summary
Techniques for rendering visual content, in response to one or more utterances, are described. A device receives one or more utterances that define a parameter(s) for desired output content. A system (or the device) identifies natural language data corresponding to the desired content, and uses natural language generation processes to update the natural language data based on the parameter(s). The system (or the device) then generates an image based on the updated natural language data. The system (or the device) also generates video data of an avatar. The device displays the image and the avatar, and synchronizes movements of the avatar with output of synthesized speech of the updated natural language data. The device may also display subtitles of the updated natural language data, and cause a word of the subtitles to be emphasized when synthesized speech of the word is being output.