Voice Dialogue System with Skip Signal Detection and History-Based Priority
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Solution Overview
Problem
Existing voice dialogue systems lack efficiency in managing user interactions, particularly in determining and executing operations based on user intent without explicit voice input, leading to suboptimal user experience.
Innovation Solution
A voice dialogue system that includes a detection unit for recognizing a voice skip signal, an acquisition unit to determine high-priority operations based on execution history, and a generation unit to output corresponding voice data, allowing the system to execute frequently performed operations automatically when a voice skip signal is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the voice dialogue system requires explicit voice input for every operation, then the system maintains high accuracy in understanding user intent, but the operation time and user effort increase significantly
Solution Approach 1:
The system performs preliminary actions by storing operation histories and predicting user intent before explicit voice input is given. When a voice skip signal is detected, the system automatically executes the predicted operation without waiting for explicit voice confirmation, thereby reducing operation time and user effort while maintaining accuracy through historical data analysis
2Productivity
If the system automatically executes operations based on history without voice input, then the operation time decreases and efficiency improves, but the reliability of executing the correct operation may deteriorate
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring operation histories and updating predictions based on accumulated data. The voice skip signal serves as a feedback trigger that confirms user intent before automatic execution, ensuring that the system only executes operations that align with actual user preferences, thereby maintaining high reliability while improving dialogue efficiency
3Measurement precision
If the system stores and analyzes detailed operation histories, then the accuracy of predicting user intent improves, but the device complexity increases
Solution Approach 1:
The system applies self-service by automatically managing operation histories and intent predictions without requiring external intervention. The history storage unit and prediction unit work autonomously to accumulate data, analyze patterns, and execute operations based on voice skip signals, reducing the need for complex external processing while maintaining high intent recognition accuracy through self-learned user behavior patterns
Data Source
AI summary
A voice dialogue system executing an operation command inputted by a voice dialogue user which stores a history of the number of times each operation is executed. Upon the reception or detection of a voice skip signal during voice input, the system ignores or skips the current voice input and acquires or retrieves an operation name with a high priority based on the history of the number of executions. The acquired operation name is then read aloud by a generation unit.