Adaptive Controller for Vehicle Speech Recognition
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Solution Overview
Problem
Current speech recognition systems in vehicles lack adaptability to user behavior and environmental conditions, leading to suboptimal performance in task completion rates, dialog time, and user confirmation rates.
Innovation Solution
Implementing a statistical process control method that monitors adaptive features such as task completion rate, dialog time, and confirmation rate, using an adaptive controller to create control charts and adjust the speech recognition system based on identified performance deviations, thereby optimizing user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a speech recognition system operates without adaptive control, then the system structure remains simple, but the task completion rate is suboptimal
Solution Approach 1:
The patent implements statistical process control with control charts that continuously monitor adaptive features (task completion rate, dialog time, confirmation rate) and provide feedback to an adaptive controller. This feedback mechanism enables the system to detect performance deviations and trigger adjustments, thereby improving task completion rates while maintaining a manageable level of complexity through structured monitoring rather than uncontrolled adaptation.
Solution Approach 2:
The system dynamically adjusts speech recognition parameters based on monitored adaptive features. When control chart analysis detects unexpected performance, the adaptive controller modifies system parameters such as recognition sensitivity, dialog flow, or confirmation thresholds. This parameter adaptation allows the system to optimize task completion rates without requiring complete system redesign.
2Duration of action of moving object
If the speech recognition system uses fixed parameters, then the system is easier to control, but the dialog time increases due to lack of adaptation
Solution Approach 1:
The patent transforms the static speech recognition system into a dynamic one by implementing continuous monitoring of adaptive features and real-time parameter adjustment. The system adapts its behavior based on observed performance metrics, allowing dialog time to be optimized for different users and contexts while maintaining controllability through the structured statistical process control framework.
Solution Approach 2:
The adaptive controller automatically adjusts system parameters based on performance data without requiring manual intervention. The statistical process control mechanism self-regulates by detecting deviations through control charts and triggering appropriate adjustments, reducing dialog time through autonomous adaptation while keeping the system easy to operate.
3Productivity
If the speech recognition system does not monitor adaptive features, then the system complexity is reduced, but the user confirmation rate increases
Solution Approach 1:
The patent implements monitoring of adaptive features including task completion rate, dialog time, and confirmation rate. This feedback loop allows the system to identify when user confirmations are excessive and trigger adjustments to reduce them. The structured statistical process control approach manages the complexity of monitoring by using control charts and predefined adjustment rules.
Solution Approach 2:
The patent replaces manual tuning and adjustment mechanisms with automated statistical process control. Instead of manually monitoring and adjusting speech recognition parameters, the system uses statistical methods and control algorithms to automatically detect performance issues and implement corrections, reducing user confirmations while managing complexity through automation.
4Adaptability or versatility
If the speech recognition system lacks adaptive control, then the device complexity is lower, but the overall user experience deteriorates
Solution Approach 1:
The system adapts to user preferences and environmental conditions by dynamically changing speech recognition parameters. The adaptive controller modifies recognition sensitivity, dialog flow, and confirmation requirements based on monitored performance and user behavior patterns. This parameter adaptation enhances user experience quality while managing complexity through focused adjustment of key parameters rather than complete system redesign.
Data Source
AI summary
A method and system can control a speech recognition system in a vehicle. The method includes monitoring adaptive feature data about interactions between a user and the speech recognition system. The method includes determining a first group of samples of the adaptive feature data and creating a control chart based on the first group of samples. The control chart includes a control limit. The method further includes determining a second group of samples of the adaptive feature data after creating the control chart. Furthermore, the method includes calculating an arithmetic mean of each sample of the second group of samples to determine a sample mean, comparing the sample mean to the control limit in order identify unexpected performance of the speech recognition system. The method includes adjusting the speech recognition system based on the identified unexpected performance if the unexpected performance is identified.