Wearable Audio Situational Detection for External Sound Enhancement
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Solution Overview
Problem
Current wearable audio devices lack the ability to dynamically modify external audio in response to specific situations, such as enhancing or diminishing certain audio sources based on environmental conditions or user preferences, which can lead to poor audio experience in noisy or complex environments.
Innovation Solution
A processing system within wearable audio devices captures sensor data, including audio and potentially visual inputs, and applies situational detection models to modify external audio data in real-time, enhancing or diminishing specific audio sources based on detected situations, such as voices of known individuals or safety announcements, using machine learning and AI techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If wearable audio devices present all external audio sources equally, then the device complexity remains low, but the audio experience deteriorates in noisy or complex environments
Solution Approach 1:
The patent segments external audio into multiple audio sources using source separation technology. Each audio source is independently identified and processed, allowing selective enhancement or suppression of specific sounds while maintaining overall audio quality. This segmentation enables the device to improve audio experience in complex environments without requiring complete system redesign.
Solution Approach 2:
The patent applies different processing qualities to different audio sources based on their importance. Important audio sources (e.g., speech, safety announcements) receive enhanced processing and amplification, while less important sources maintain original quality or are suppressed. This local quality differentiation improves overall audio experience while managing computational complexity efficiently.
2Ease of operation
If wearable audio devices enhance specific audio sources selectively, then the audio experience improves, but the device complexity increases due to situational detection models
Solution Approach 1:
The patent implements a multi-functional processing system that performs audio capture, source separation, situational detection, and selective enhancement through a unified architecture. The same processing pipeline handles multiple audio sources and various situations (conversations, safety announcements, noise reduction), reducing overall system complexity despite the advanced capabilities provided.
Solution Approach 2:
The situational detection models automatically identify and classify audio sources without user intervention. The system self-adjusts audio enhancement parameters based on detected situations, eliminating the need for manual user configuration and reducing the complexity of user interface management while maintaining high audio experience quality.
3Ease of operation
If wearable audio devices apply situational detection models to modify external audio, then relevant audio sources are amplified, but background noise reduction may diminish important sounds
Solution Approach 1:
The patent employs feedback mechanisms where the system continuously monitors audio sources and adjusts enhancement levels based on situational context. The situational detection models provide feedback about the current audio environment, allowing the system to dynamically adjust which sources are amplified and to what extent, ensuring important sounds are preserved while reducing background noise.
Solution Approach 2:
The patent dynamically changes audio processing parameters (gain, amplification level, frequency response) based on the type of audio source detected. Different parameter sets are applied to different situations: speech sources receive specific enhancement parameters, safety announcements receive different parameters, and background noise receives suppression parameters. This parameter adaptation prevents important sounds from being diminished while reducing unwanted noise.
Data Source
AI summary
A processing system including at least one processor may capture data from a sensor comprising a microphone of a wearable device, the data comprising external audio data captured via the microphone, determine first audio data a first audio source in the external audio data, apply the first audio data to a situational detection model, and detect a first situation via the first situational detection model. The processing system may then modify, in response to detecting the first situation via the first situational detection model, the external audio data via a change to the first audio data in the external audio data to generate a modified audio data, in accordance with at least a first audio adjustment corresponding to the first situational detection model, where the modifying comprises increasing or decreasing a volume of the first audio data, and present the modified audio data via an earphone of the wearable device.