Vehicle Driving Noise Prediction for Speech Recognition
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Solution Overview
Problem
Modern vehicles face challenges in distinguishing driving noise from uneven road surfaces, which affects the quality of automatic speech recognition systems, leading to errors in voice command interpretation and noise misclassification.
Innovation Solution
A method using sensors like cameras, laser scanners, or radar systems to predict and characterize driving noise from road unevenness and surface structures, allowing for real-time correction of microphone signals to improve speech recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If speech recognition systems process microphone signals in vehicles, then voice control functionality is enabled, but speech recognition quality deteriorates due to external driving noise from road unevenness
Solution Approach 1:
The system performs preliminary identification of driving noise segments before they interfere with speech recognition. By detecting road unevenness patterns and predicting noise occurrence in advance, the system can pre-adjust noise suppression parameters and temporarily adjust or deactivate speech recognition during predicted noise periods, preventing degradation rather than reacting after damage occurs.
Solution Approach 2:
The patent introduces an intermediary noise identification and analysis module between the microphone signal source and the speech recognition system. This intermediary component analyzes microphone signals to identify driving noise segments, separates them from speech signals, and provides cleaned signals to the speech recognition system, thereby protecting the latter from noise interference while maintaining voice control functionality.
2Measurement precision
If the system distinguishes driving noise from speech signals, then speech recognition accuracy improves, but system complexity increases due to additional noise analysis requirements
Solution Approach 1:
The system achieves multi-functionality by using the existing microphone array for both speech recognition and driving noise identification. The same hardware infrastructure serves dual purposes: capturing speech signals for voice control and detecting driving noise patterns for segmentation. This eliminates the need for separate dedicated noise sensors, reducing overall system complexity while maintaining high speech recognition accuracy.
Solution Approach 2:
The noise identification system serves itself by using the microphone signals already present in the system. Rather than requiring external sensors or additional input channels, the system analyzes the existing microphone data to identify and characterize driving noise segments, making the noise analysis capability self-contained and reducing dependency on additional complex hardware components.
3Ease of operation
If the system responds to detected road unevenness, then driving comfort improves through forced braking and suspension adjustment, but response time is reduced due to real-time processing requirements
Solution Approach 1:
The system identifies and flags road unevenness segments in advance before the vehicle actually encounters them. By detecting patterns in microphone signals that indicate upcoming noise-generating conditions, the system can trigger preventive measures such as suspension pre-adjustment or driver warning before the noise occurs, optimizing both comfort and response timing without requiring reactive delays.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively reduces speech recognition errors by predicting and compensating for driving noise, ensuring accurate voice command interpretation and enhancing telecommunications quality by cleaning sound signals of noise components in real-time.
Implementation Method 1
A segment of the road lying ahead of the vehicle in the direction of travel is observed with a sensor installed in or on the vehicle
Implementation Method 2
a sound signal acquired by a microphone disposed in a vehicle
Data Source
AI summary
The disclosure concerns a method for recognizing driving noise in a sound signal that is acquired by a microphone disposed in a vehicle. The sound signal originates from the surface structure of the road. According to the disclosure, a segment of the road lying ahead of the vehicle in the direction of travel is observed with a sensor installed in or on the vehicle. Using the observation data obtained, the start and duration of driving noise originating from the surface structure of the road are predicted.