Speech Interaction System With User Attribute Recognition
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Solution Overview
Problem
Existing speech interaction systems lack flexibility in responding to speech content, as they perform consistent operations for consistent speech content, resulting in limited forms of response and failure to cater to individual user attributes.
Innovation Solution
A speech interaction method and apparatus that performs user attribute recognition in conjunction with content recognition, allowing for weighted user attribute determination and vocabulary-based responses tailored to individual user attributes, such as gender and age, to provide varied responses for the same speech content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If consistent operations are performed for consistent speech content, then system reliability is maintained, but response flexibility and adaptability to user attributes deteriorate
Solution Approach 1:
The system segments the speech processing into independent modules: user attribute recognition module and content recognition module. Each module processes specific aspects separately, allowing flexible combination of results without increasing overall system complexity. The attribute recognition and content recognition are divided into independent functional blocks that can operate in parallel.
Solution Approach 2:
The speech interaction system is designed with multi-functionality to handle both user attribute identification and content understanding through a unified architecture. The same speech data is processed by multiple recognition modules that serve different purposes, enabling the system to provide personalized responses while maintaining a cohesive system structure.
2Adaptability or versatility
If user attribute recognition is added to content recognition, then response personalization improves, but processing time increases
Solution Approach 1:
The user attribute recognition is performed in advance as a preliminary action before content recognition. By identifying user attributes early in the processing pipeline, the system can prepare personalized response templates and vocabulary lists beforehand, reducing the time needed during the actual content processing and response generation phases.
Solution Approach 2:
The system maintains continuous processing by executing user attribute recognition and content recognition in an overlapping manner. While one module processes speech data, the other module prepares response templates based on recognized attributes, ensuring that both operations proceed simultaneously without creating idle time or significant delays.
3Measurement precision
If multiple recognition modules are employed, then recognition accuracy improves, but system complexity increases
Solution Approach 1:
Multiple recognition modules (user attribute recognition and content recognition) are merged into a unified processing framework that shares common resources such as speech data input, processing architecture, and response generation mechanisms. This combining approach allows the system to leverage multiple recognition perspectives while avoiding the complexity of completely separate independent systems.
Data Source
AI summary
The present invention discloses a speech interaction method and apparatus, and pertains to the field of speech processing technologies. The method includes: acquiring speech data of a user; performing user attribute recognition on the speech data to obtain a first user attribute recognition result; performing content recognition on the speech data to obtain a content recognition result of the speech data; and performing a corresponding operation according to at least the first user attribute recognition result and the content recognition result, so as to respond to the speech data. According to the present invention, after speech data is acquired, user attribute recognition and content recognition are separately performed on the speech data to obtain a first user attribute recognition result and a content recognition result, and a corresponding operation is performed according to at least the first user attribute recognition result and the content recognition result.