Adaptive Audio Signal Processing for Context-Dependent Noise Cancellation
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Solution Overview
Problem
Conventional speech processing systems are ill-suited for various audio contexts, leading to suboptimal performance in noise cancellation and signal processing, particularly between human users and devices such as speech recognition systems.
Innovation Solution
An adaptive audio input device that selects signal profiles based on the audio context, using a signal processor and selector to determine the appropriate processing for either user-to-user or user-to-device interactions, incorporating noise cancellation, filtering, and frequency adjustments to optimize audio quality for the intended sink.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional signal processing is applied, then processing is performed, but performance is suboptimal for specific audio contexts
Solution Approach 1:
The system dynamically selects signal processing profiles based on the detected audio context. The audio context detector identifies whether the context is user-to-user or user-to-device, and the signal processor applies different profiles accordingly, making the processing adaptive rather than static.
Solution Approach 2:
The system changes processing parameters by selecting different signal processing profiles. Each profile contains specific parameter settings optimized for its target context, such as different noise cancellation strengths or frequency adjustments, allowing the system to adapt to different audio scenarios.
2Reliability
If single signal processing profile is used, then device complexity is reduced, but performance for multiple audio contexts deteriorates
Solution Approach 1:
The signal processing system is segmented into multiple independent profiles, each optimized for a specific audio context. The audio context detector segments the processing decision by identifying the current context type, and the signal processor applies the corresponding segmented profile, avoiding the need for a single complex universal processor.
Solution Approach 2:
The signal processing system achieves multi-functionality by incorporating multiple profiles within a single device. The same hardware processor can switch between different processing profiles (user-to-user, user-to-device) based on context detection, making one device serve multiple specialized functions without requiring separate hardware for each context.
3Reliability
If noise cancellation is applied, then audio clarity for human users is improved, but signal fidelity for devices deteriorates
Solution Approach 1:
The system applies local quality optimization by using different noise cancellation strengths for different contexts. For user-to-user communication, stronger noise cancellation is applied to enhance perceived audio clarity for human ears. For user-to-device communication, weaker noise cancellation is applied to preserve signal fidelity for automated processing, recognizing that devices can tolerate more background noise than humans can.
Data Source
AI summary
Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.