Text-to-Video Interactive Training System for Branching Conversations
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Solution Overview
Problem
Geographically-distributed employees face challenges in consistently delivering polished corporate messaging during face-to-face or live telephone-based customer interactions due to resource-intensive training methods that are not effectively verified for knowledge absorption.
Innovation Solution
A computer-implemented method that processes text strings with branching moments to generate executable code and media elements for a virtual respondent, enabling self-coaching training experiences by converting text into computer-generated audio and video, allowing for interactive and adaptive conversational simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If intensive boot camp training programs are used for geographically-distributed employees, then training coverage can be provided, but the resource intensity and inability to verify knowledge absorption worsen
Solution Approach 1:
The patent creates virtual copies of human respondents (virtual actors) that can be replicated and distributed to multiple trainees simultaneously. These virtual respondents are generated from text strings and can be deployed across numerous client devices, eliminating the need for physical boot camp sessions while maintaining training coverage. The virtual respondents can be instantiated repeatedly without additional resource costs.
Solution Approach 2:
The training system enables self-coaching experiences where employees independently interact with virtual respondents at their own pace and location. The system automatically tracks interactions, evaluates responses, and verifies knowledge absorption without requiring instructor presence or manual assessment, thereby reducing resource intensity while maintaining training effectiveness.
2Adaptability or versatility
If virtual actors are generated with branching conversation moments, then interactive training effectiveness improves, but computational resource usage increases
Solution Approach 1:
The system pre-processes text strings containing branching conversation moments into structured formats (such as JSON) before deployment. This preliminary processing identifies and structures all possible conversation branches in advance, allowing the virtual respondents to efficiently retrieve and present appropriate responses during interactions without performing complex real-time analysis, thereby reducing computational resource usage during actual training sessions.
3Extent of automation
If automated conversion of text to executable code is implemented, then training scenario automation improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary processing layer that converts natural language text strings into structured executable formats (such as JSON with predefined schemas). This intermediary step automates the creation of training scenarios by translating human-readable text into machine-executable code without requiring complex programming logic, thereby improving automation while managing system complexity through standardized conversion processes.
Data Source
AI summary
Computer implemented techniques for converting a text string to an interactive media. The techniques cause a data processing system to receive a text string having one or more branching moments, process the text string to recognize indications of the one or more branching moments given the text string, convert the processed text string and the indications of the one or more branching moments into executable computer code, receive a response to a given one of the converted one or more branching moments from a predetermined set of responses, generate, from the executable computer code and media elements for the response, a virtual respondent, and store the executable computer code and the media elements as a file in the computer storage that represents the virtual respondent.