Mobile Dialogue Enhancement Using Non-Acoustic Scene Sensing
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Solution Overview
Problem
Existing environment-aware audio processing techniques for mobile devices rely heavily on acoustic data, which are inadequate in dynamically changing environments, leading to suboptimal audio quality.
Innovation Solution
Utilize non-acoustic sensors like accelerometers, gyroscopes, and GPS to gather context information, process and classify mobility scenes, and adjust audio processing parameters accordingly to enhance dialogue intelligibility in diverse environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If acoustic-based methods are used for environment-aware processing, then audio processing can be performed, but the processing performance is suboptimal in dynamically changing environments
Solution Approach 1:
The patent segments the environmental sensing task by using multiple independent non-acoustic sensors (accelerometer, gyroscope, GPS, barometer) to capture different aspects of the environment. Each sensor provides specific information that, when combined, creates a comprehensive environmental profile for more reliable and adaptable audio processing.
Solution Approach 2:
The patent merges non-acoustic sensor data with acoustic data to create a fused environmental understanding. This combination allows the system to overcome the limitations of acoustic-only methods by incorporating context from motion, location, and atmospheric pressure sensors, thereby improving both reliability and adaptability.
2Adaptability or versatility
If non-acoustic sensor data is used for environment-aware processing, then environmental adaptability is improved, but device complexity increases
Solution Approach 1:
The patent makes existing mobile device sensors multi-functional by using them not only for their primary purposes (e.g., accelerometer for screen orientation) but also for environmental scene classification. This approach improves adaptability without adding dedicated hardware complexity.
Solution Approach 2:
The patent introduces an intermediary processing layer that fuses data from multiple sensors and translates it into environmental scene information. This intermediary layer manages the complexity by providing a unified interface between diverse sensors and the audio processing system, making the overall system more manageable despite the increased sensor input.
3Measurement precision
If scene classification based on non-acoustic sensors is implemented, then dialogue intelligibility is improved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary classification of environmental scenes using non-acoustic sensor data before audio processing. By pre-establishing the environmental context (e.g., identifying that the device is in a moving vehicle or outdoors), the system can pre-configure appropriate audio processing parameters, reducing real-time processing time while maintaining high dialogue intelligibility.
Solution Approach 2:
The patent implements dynamic scene classification that adapts to changing environmental conditions in real-time. The system continuously monitors non-acoustic sensor data and dynamically adjusts audio processing parameters based on the current scene, optimizing the balance between processing time and dialogue intelligibility as conditions change.
Data Source
AI summary
Described herein is a method of performing environment-aware processing of audio data for a mobile device. In particular, the method may comprise obtaining non-acoustic sensor information of the mobile device. The method may further comprise determining scene information indicative of an environment of the mobile device based on the non-acoustic sensor information. The method may yet further comprise performing audio processing of the audio data based on the determined scene information.