Vehicle Sound Signal Processing Spatial Filtering Noise Separation
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Solution Overview
Problem
Existing voice recognition systems in vehicles face challenges in accurately extracting user voice commands from mixed signals, including engine sounds and passenger voices, due to poor separation performance and high computational burden.
Innovation Solution
A sound signal processing method and apparatus that employs spatial filtering, using a spatial filter to separate target signals from noise, and a mask application unit to enhance signal selectivity, incorporating techniques like beam-forming, Independent Component Analysis, and Minimum power distortionless response, to improve voice command recognition with reduced computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional voice recognition systems are used to extract user voice commands from mixed signals, then the system can process voice inputs, but the separation performance is poor and voice recognition accuracy deteriorates due to engine sounds and passenger voices interfering
Solution Approach 1:
The patent segments the mixed sound signals into different spatial components by dividing the signal processing into multiple channels corresponding to different microphone positions. Each channel processes signals from specific spatial directions, separating target voice commands from background noises and passenger voices through spatial segmentation of the audio spectrum
Solution Approach 2:
The patent applies local quality by enhancing specific spatial regions where target voice signals are located while suppressing other regions containing noise. The signal processing selectively amplifies signals from the direction of the user's voice while attenuating signals from other directions, creating localized quality enhancement in the desired audio sector
2Measurement precision
If advanced signal processing techniques are applied to improve signal separation, then voice recognition accuracy improves, but computational burden increases
Solution Approach 1:
The patent applies partial action by selectively processing only the frequency bands and spatial regions that contain relevant voice signals, rather than processing the entire audio spectrum uniformly. This approach achieves adequate signal separation for voice recognition while avoiding excessive computational effort on irrelevant signal components
Solution Approach 2:
The patent changes parameters such as spatial filter coefficients and frequency weighting factors to optimize the balance between separation performance and computational complexity. By dynamically adjusting these parameters based on the acoustic environment, the system achieves effective noise suppression without requiring excessively complex processing algorithms
Data Source
AI summary
A sound signal processing method, the sound signal processing apparatus and the vehicle equipped with the apparatus, in which the sound signal processing apparatus includes a spatial filtering unit configured to obtain a filtered signal including a target signal by a spatial filtering by applying a spatial filter to an input signal, and a mask application unit configured to obtain an output signal by applying a mask to the filtered signal. The mask may be obtained by using a spatial selectivity between the target signal and noise of the target signal.