AI Dynamic Microphone Layout for In-Car Voice Noise Separation
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Solution Overview
Problem
Current vehicle technologies do not adequately support passenger interaction with the external environment in non-, partially-, and fully-autonomous vehicles, posing safety risks as users accustomed to interacting with external environments in autonomous vehicles may not adjust their behavior in non-autonomous vehicles, leading to potential hazards.
Innovation Solution
A dynamic microphone system utilizing multiple microphones and artificial intelligence for accurate voice command recognition, noise cancellation, and speech processing, enabling passengers to interact with autonomous vehicles through voice commands while reducing environmental noise interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple microphones and AI processing are added to enable accurate voice recognition, then voice command recognition accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the voice recognition task into multiple processing stages: multiple microphones capture audio signals separately, then AI processing separates and identifies individual voices, and finally speech recognition extracts commands. This segmentation allows accurate multi-speaker identification while managing system complexity through modular processing.
Solution Approach 2:
The microphone system is designed to perform multiple functions: capturing voice commands, identifying multiple speakers, canceling environmental noise, and recognizing speech patterns. This multi-functionality consolidates what would otherwise require separate systems into a single integrated solution, improving accuracy without proportionally increasing complexity.
2Measurement precision
If noise cancellation processing is applied to voice commands, then voice recognition accuracy is improved, but processing time increases
Solution Approach 1:
The system performs noise cancellation and voice separation as preliminary processing steps before speech recognition. By pre-processing the audio signals to remove environmental noise and isolate speaker voices, the system reduces the computational burden during the final recognition phase, balancing accuracy with processing efficiency.
3Measurement precision
If speaker identification and noise cancellation are performed, then passenger voice identification accuracy is improved, but computational resources required increase
Solution Approach 1:
The system uses AI processing as an intermediary layer between raw microphone signals and final speech recognition. This intermediary performs voice separation and speaker identification, creating cleaner input for the speech recognition engine. This approach distributes computational load across specialized processing stages, improving accuracy while managing energy consumption through efficient algorithm design.
Data Source
AI summary
Devices, systems and processes for a dynamic microphone system that enhances the passenger experience in autonomous vehicles are described. One example method for enhancing a passenger experiences includes generating, using an artificial intelligence algorithm, a plurality of filters based on a plurality of stored waveforms previously recorded by each of one or more passengers and a plurality of recordings of one or more noise sources, capturing voice commands from at least one of the one or more passengers inside the autonomous vehicle, generating voice commands with reduced distortion based on processing the voice commands using the plurality of filters, and instructing, based on the voice commands with reduced distortion, the autonomous vehicle to perform one or more actions.