Vehicle Voice Control Microphone Selection via Correlation Analysis
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Solution Overview
Problem
Existing motor-vehicle voice-control systems face challenges in accurately selecting the optimal microphone for operation, especially in varying acoustic conditions, leading to reduced accuracy and longer reaction times.
Innovation Solution
A voice-control system with multiple microphones and an evaluation unit that calculates correlation coefficients, energy values, and delay times to select the optimal microphone based on these parameters, using methods like window functions and fast Fourier transforms to determine the best-suited microphone for operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple microphones are used to improve voice control accuracy, then the reliability of voice recognition is improved, but the device complexity increases
Solution Approach 1:
The system divides the microphone array into multiple individual microphones (at least two) that can be independently evaluated. Each microphone is assessed based on correlation coefficients with voice signals, allowing the system to segment the overall voice recognition task into separate microphone evaluations and select the optimal one.
Solution Approach 2:
The evaluation unit continuously monitors the output of each microphone and uses feedback mechanisms to compare correlation coefficients. Based on this feedback, the system dynamically selects which microphone to use for voice recognition, improving reliability while managing complexity through intelligent selection rather than processing all microphones simultaneously.
2Measurement precision
If the system evaluates multiple microphones to select the optimal one, then the measurement precision of voice signals is improved, but the reaction time increases
Solution Approach 1:
The system performs preliminary evaluation of multiple microphones by calculating correlation coefficients in advance, even before a voice command is received. This preliminary action allows the system to have pre-identified optimal microphones ready for immediate use, reducing reaction time when actual voice recognition is needed while maintaining high measurement precision.
Solution Approach 2:
The system replaces complex mechanical or sequential microphone switching mechanisms with electronic signal processing. By using correlation coefficient calculations and digital signal analysis, the system can rapidly evaluate multiple microphones and switch between them electronically, significantly reducing reaction time compared to mechanical switching while maintaining precision.
3Measurement precision
If correlation coefficients are calculated for multiple microphone pairs, then the accuracy of microphone selection is improved, but the computational complexity increases
Solution Approach 1:
The system calculates correlation coefficients for multiple microphone pairs (at least one correlation pair involving at least two microphones) to thoroughly evaluate each microphone's performance. By performing this partial analysis on each microphone pair and then synthesizing the results, the system achieves high selection accuracy while managing computational complexity through structured evaluation rather than exhaustive processing of all possible combinations.
Data Source
AI summary
A voice-control system for motor vehicles has a plurality of spaced microphones emitting respective microphone signals, and an evaluation unit connected to the microphones. This unit serves for assembling correlation pairs from the signals of two of the microphones, calculating a correlation coefficient for each correlation pair, detecting an energy value for each microphone, detecting a respective delay time of a voice signal between a voice signal source and the each of the microphones, and selecting in dependence on current correlation coefficients of the correlation pairs, on the current energy values of the microphones, and on the current delay time of the voice signal to the microphones, that microphone whose signal is optimal as a basis for the operation of the voice-control system.