Vehicle Speech Recognition Noise Filtering via Acoustic Model Adaptation
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Solution Overview
Problem
Voice-activated vehicle systems face challenges in accurately recognizing speech commands due to distortion from non-speech related sounds, such as engine noise, external noises, and audio system sounds, which reduces the clarity and decipherability of voice commands.
Innovation Solution
The system utilizes sound-related vehicle information, like engine RPM, HVAC settings, and external noise levels, to generate an interference profile record, which is used to modify the speech recognition process by applying filters and adapting acoustic models to enhance speech recognition and audio output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech recognition is performed in vehicle environments, then voice commands can be processed, but non-speech related sounds (engine noise, external noises, audio system sounds) distort speech commands and reduce recognition accuracy
Solution Approach 1:
The patent segments the audio signal into speech components and non-speech components (noise) using spectral subtraction and adaptive filtering. The speech recognition system processes only the separated speech signal, effectively isolating it from interfering vehicle noises, engine sounds, and external audio system sounds.
Solution Approach 2:
The patent introduces an intermediary noise estimation and cancellation module between the microphone input and speech recognition system. This intermediary component estimates background noise characteristics and subtracts them from the input signal, serving as a mediator that protects the speech recognition system from harmful noise while preserving speech integrity.
2Reliability
If traditional speech recognition systems are used in vehicles, then basic voice commands can be recognized, but the clarity and decipherability of voice commands are reduced by overpowering non-speech sounds
Solution Approach 1:
The patent implements feedback mechanisms where the noise estimation module continuously monitors the audio environment and adjusts its noise profile based on recent signal characteristics. This feedback loop allows the system to adapt to changing noise conditions (engine acceleration, HVAC changes, radio volume adjustments) and maintain reliable speech recognition throughout the vehicle operation cycle.
Solution Approach 2:
The patent performs preliminary noise estimation and spectral subtraction before the speech recognition process begins. By pre-processing the audio signal to remove estimated noise components in advance, the system ensures that the speech recognition module receives a cleaner signal, improving reliability before recognition attempts are made.
Data Source
AI summary
An audio signal may be received, in a processor associated with a vehicle. Sound related vehicle information representing one or more sounds may be received by the processor. The sound related vehicle information may or may not include an audio signal. A speech recognition process or system may be modified based on the sound related vehicle information.