Dynamic Noise Suppression Algorithm for Hands-Free Speech Recognition
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Solution Overview
Problem
Current hands-free speech recognition systems in vehicles struggle to adapt to changing ambient noise levels, which can impair the recognition of spoken words during vehicle operations, such as driving, climate control, audio-device usage, and external conditions like weather, leading to suboptimal communication quality.
Innovation Solution
A method and system that receive and process vehicle condition inputs to create a noise parameter, which is used to adjust the noise suppression algorithm of the speech recognition system, thereby enhancing the system's ability to filter out ambient noise and improve speech recognition accuracy in dynamic vehicular environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed noise suppression algorithm is used in the speech recognition system, then the system structure remains simple, but the speech recognition accuracy deteriorates when ambient noise levels change due to varying vehicle conditions
Solution Approach 1:
The patent implements dynamic tuning of the noise suppression algorithm by continuously adjusting algorithm parameters based on real-time vehicle condition inputs. The system transitions from a fixed algorithm to a dynamic one that adapts its noise suppression characteristics according to changing ambient noise levels caused by vehicle speed, fan operations, audio devices, and road conditions, thereby maintaining high speech recognition accuracy across varying operational environments
Solution Approach 2:
The system changes the parameters of the noise suppression algorithm based on vehicle condition inputs. By monitoring parameters such as vehicle speed, fan level, audio-device status, and road type, the system adjusts the noise suppression algorithm's parameters dynamically to match the current ambient noise profile, resolving the contradiction between maintaining simple system structure and achieving high recognition accuracy under varying conditions
2Reliability
If the noise suppression algorithm is dynamically adjusted based on multiple vehicle condition inputs, then speech recognition accuracy improves in changing environments, but the system complexity and data processing requirements increase
Solution Approach 1:
The hands-free system is enhanced with multi-functionality by integrating multiple vehicle condition sensors and a comprehensive noise suppression algorithm that handles various noise sources. The system universally processes inputs from vehicle speed sensors, fan controllers, audio-device monitors, and road condition detectors, consolidating these diverse functions into a unified noise suppression framework that improves communication reliability without requiring separate systems for each function
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring vehicle condition inputs and using this information to adjust the noise suppression algorithm in real-time. The feedback loop captures changes in ambient noise levels caused by varying vehicle operations and feeds this information back to the algorithm, which then adapts its parameters accordingly, ensuring reliable speech recognition throughout the communication process
Data Source
AI summary
A method of tuning a hands-free system in a mobile vehicle, the method including receiving a plurality of vehicle condition inputs, creating a noise parameter based on the vehicle condition inputs and adjusting a noise suppression algorithm of the hands-free system based on the created noise parameter.