Wearable Audio Ducking for Real-Time Speech Awareness
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Solution Overview
Problem
Users of wearable audio devices face inconvenience when transitioning from a private audio experience to real-world interactions, as they need to manually adjust volume or pause music to hear conversations, due to the lack of automatic audio ducking functionality.
Innovation Solution
A wearable device equipped with microphones and processing capabilities that detect ambient noise to automatically duck audio playback when user speech is detected, and continue ducking based on ambient speech, allowing for seamless transitions between private listening and conversation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise-cancelling functionality is activated to provide private audio experience, then audio isolation is improved, but ambient awareness deteriorates
Solution Approach 1:
The system dynamically switches between noise-cancelling mode and ambient pass-through mode based on detected speech patterns. When user speech is detected, the system transitions from active noise cancellation to allowing ambient sounds through, enabling automatic adaptation to conversation scenarios without manual intervention.
Solution Approach 2:
The system uses microphones to continuously monitor ambient sounds and detect speech patterns. This feedback loop allows the system to identify when the user is speaking or being spoken to, and automatically adjust the audio output accordingly by pausing or reducing volume of playback content during detected conversations.
2Measurement precision
If manual volume adjustment is required for conversations, then audio control precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system automatically detects speech patterns and autonomously adjusts audio playback volume or pauses content without requiring manual user intervention. The speech detection algorithm identifies conversation start and end points, and the system self-manages the audio output accordingly.
Solution Approach 2:
The patent replaces manual mechanical volume control with an automated electronic system that uses speech pattern recognition and signal processing. Instead of requiring physical adjustment of volume controls, the system uses algorithms to detect speech and automatically modify audio output levels.
3Productivity
If audio playback continues during conversations, then productivity is improved, but speech intelligibility deteriorates
Solution Approach 1:
The system continuously monitors ambient audio through microphones and uses speech detection algorithms to identify when conversations are occurring. This feedback enables the system to pause or reduce volume of playback content during detected speech events, ensuring speech intelligibility while resuming normal playback when no conversation is detected.
Solution Approach 2:
The audio playback system dynamically adjusts its behavior based on real-time speech detection. During detected conversations, the system transitions to a paused or attenuated state, and automatically returns to normal playback after the conversation ends, maintaining both productivity and speech intelligibility as needed.
Data Source
AI summary
An example implementation may involve driving an audio output module of a wearable device with a first audio signal and then receiving, via at least one microphone of wearable device, a second audio signal comprising first ambient noise. The device may determine that the first ambient noise is indicative of user speech and responsively duck the first audio signal. While the first audio signal is ducked, the device may detect, in a subsequent portion of the second audio signal, second ambient noise, and determine that the second ambient noise is indicative of ambient speech. Responsive to the determination that the second ambient noise is indicative of ambient speech, the device may continue the ducking of the first audio signal.