Relationship-Driven Virtual Assistant With Voice Copy Retrieval
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Solution Overview
Problem
Existing virtual assistants lack personalization in responses, often providing generic voices or holograms that are not familiar to the user, lacking the personal touch needed for effective interaction in home or office environments.
Innovation Solution
A system that records personalized voices and interactions between users, learns relationships, and delivers responses in the voice or hologram of the associated user, enhancing personalization and familiarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generic voices or holograms are used for virtual assistant responses, then the system can provide standardized responses efficiently, but the personalization and user familiarity are reduced
Solution Approach 1:
The system creates and stores voice copies of multiple users in a database. When a query is received, the system selects an appropriate user copy based on the relationship between the query and stored user interactions, then transmits the response using that copied voice. This allows personalized responses without requiring real-time voice synthesis for each user.
Solution Approach 2:
The system performs preliminary actions by capturing and storing voice data and user interactions in advance. The database is pre-populated with user voices and their associated interactions, enabling the system to quickly retrieve and reproduce appropriate responses without delay when users actually need assistance.
2Adaptability or versatility
If the system stores and processes user interaction data to determine relationships, then personalization improves, but the device complexity increases
Solution Approach 1:
The system automatically determines relationships between queries and users by analyzing stored interactions without requiring manual input or complex external processing. The database structure itself enables the system to self-determine relationships by comparing query characteristics against stored user interaction patterns.
Solution Approach 2:
The database serves multiple functions simultaneously: it stores user voices, captures user interactions, determines relationships between queries and users, and selects appropriate responses. This multi-functionality reduces the need for separate specialized systems and simplifies the overall architecture.
Data Source
AI summary
A computer-implemented method, a computer system and a computer program product generate a query response in an environment based on predicted relationships between users. The method includes capturing a question with a device in the environment, where the question includes a speaking voice and is selected from a group consisting of: video data, audio data and text data. The method also includes identifying the speaker of the question based on the speaking voice. The method further includes determining a relationship between the question and each user interaction in a database of user interactions, where each user interaction is associated with a user. In addition, the method includes selecting a response from the database of user interactions based on the relationship. Lastly, the method includes transmitting the response to the speaker of the question in the environment, where the transmission of the response uses a voice of the user.