Vehicle Voice Command System Noise Source Elimination
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Solution Overview
Problem
Vehicle speech recognition systems face challenges in accurately capturing voice commands due to high noise levels in noisy environments, such as open windows or blower fans, leading to reduced recognition accuracy and driver frustration.
Innovation Solution
The system actively identifies and reduces noise sources by querying vehicle sensors and controllers for status information, prompting or automatically adjusting vehicle settings like window positions, fan speeds, and audio volumes to improve audio quality for better speech recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex noise cancellation algorithms are used to improve speech recognition in noisy environments, then recognition accuracy may improve slightly, but system complexity and processing requirements increase significantly
Solution Approach 1:
The patent extracts and eliminates the noise source from the system by actively controlling it, rather than attempting to filter it out through complex algorithms. The speech recognition system queries vehicle systems to identify noise sources (blower fan, windows, sunroof) and sends commands to eliminate them, thereby removing the harmful noise component before speech capture occurs.
Solution Approach 2:
The system performs preliminary noise elimination before speech recognition occurs. By proactively identifying and eliminating noise sources in advance of the speech capture process, the system prepares a cleaner acoustic environment, improving recognition accuracy without requiring complex real-time noise cancellation algorithms.
2Measurement precision
If the vehicle actively eliminates noise sources by controlling vehicle systems, then speech recognition accuracy improves, but energy consumption and system resource usage increase
Solution Approach 1:
The vehicle systems serve themselves by automatically responding to noise conditions. When the speech recognition system identifies a noise source and sends an elimination command, the vehicle system (blower fan, window controls) automatically adjusts itself without requiring continuous manual intervention or complex control algorithms, reducing overall system resource consumption.
Solution Approach 2:
The system implements a feedback loop where the speech recognition system monitors noise conditions, identifies sources, and sends commands to eliminate them. This closed-loop approach allows the system to respond only when necessary, optimizing energy consumption by eliminating noise sources selectively rather than continuously operating vehicle systems.
3Use of energy by moving object
If the system prompts the driver to eliminate noise sources manually, then energy consumption is reduced, but the process time and user burden increase
Solution Approach 1:
The system dynamically adapts its response strategy based on the situation. It can operate in an automated mode where it actively controls noise sources, or in a manual prompt mode where it requests driver action. This dynamic flexibility allows the system to optimize between energy consumption and process time depending on specific operational contexts and driver preferences.
Data Source
AI summary
A voice command acquisition method and system for motor vehicles is improved in that noise source information is obtained directly from the vehicle system bus. Upon receiving an input signal with a voice command, the system bus is queried for one or more possible sources of a noise component in the input signal. In addition to vehicle-internal information (e.g., window status, fan blower speed, vehicle speed), the system may acquire external information (e.g., weather status) in order to better classify the noise component in the input signal. If the noise source is found to be a window, for example, the driver may be prompted to close the window. In addition, if the fan blower is at a high speed level, it may be slowed down automatically.