Earphone Bone Conduction Voice Detection Mode Switching
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Solution Overview
Problem
Active noise reduction earphones require manual mode switching between noise reduction and transparent transmission modes, which is inconvenient when the user's hands are occupied, affecting user experience.
Innovation Solution
An earphone controlling method that acquires sound signals through a bone conduction element to automatically switch to transparent transmission mode when a voice signal is detected, using energy and frequency thresholds or correlation analysis with air conduction microphone signals to determine voice activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual mode switching is implemented, then the earphone can switch between noise reduction and transparent transmission modes, but the operation convenience deteriorates when user's hands are occupied
Solution Approach 1:
The earphone system performs self-service by automatically detecting voice signals through the bone conduction element and autonomously switching between noise reduction and transparent transmission modes without requiring manual user intervention. The system monitors the sound signal characteristics and automatically adjusts the working mode based on detected voice activity, thereby resolving the contradiction between mode switching capability and operation convenience.
Solution Approach 2:
The patent replaces the mechanical manual switching operation with an automated acoustic detection system. Instead of requiring physical button presses or tactile interactions, the system uses the bone conduction element to detect voice signals and automatically triggers mode switching through signal processing and control algorithms, substituting mechanical operation with acoustic-field-based automation.
2Ease of operation
If automatic voice detection is implemented using bone conduction element, then operation convenience is improved, but the complexity of detecting and measuring increases
Solution Approach 1:
The bone conduction element is utilized for multiple functions: it serves both as the primary audio output transducer for bone conduction sound transmission and as a voice detection sensor for automatic mode switching. This multi-functionality allows the system to achieve hands-free operation while leveraging the existing hardware capability for voice signal detection, thereby reducing the need for additional dedicated sensors and simplifying the overall detection system.
Solution Approach 2:
The system implements a feedback mechanism where the sound signal detected by the bone conduction element is continuously monitored and analyzed. When the detected signal characteristics indicate voice activity (based on energy thresholds or correlation analysis with air conduction microphone), the system automatically adjusts the working mode. This closed-loop feedback approach enables accurate voice detection and automatic response, resolving the detection complexity through systematic signal processing.
3Measurement precision
If energy threshold and frequency threshold methods are used for voice detection, then detection precision is improved, but the device complexity increases
Solution Approach 1:
The system employs parameter-based voice detection by analyzing specific characteristics of the sound signal, such as energy level and frequency content. By setting predetermined energy thresholds and frequency thresholds, the system can accurately distinguish voice signals from background noise. This parameter-change approach allows precise voice activity detection using relatively simple threshold comparison operations, balancing detection precision with computational efficiency and avoiding overly complex algorithms.
4Measurement precision
If correlation analysis with air conduction microphone is used, then voice detection accuracy is improved, but the device complexity and energy consumption increase
Solution Approach 1:
The system merges the detection capabilities of two different sensing paths: the bone conduction element and the air conduction microphone. By performing correlation analysis between the signals from these two sources, the system can more accurately identify voice signals and distinguish them from environmental noise. This merging of detection paths enhances voice detection accuracy by leveraging complementary information from both bone conduction and air conduction channels, while the correlation analysis provides a systematic method for combining the signals effectively.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables intelligent, hands-free mode switching, improving user experience by accurately determining voice activity and adjusting the earphone mode accordingly, ensuring clear communication while reducing noise interference.
Implementation Method 1
acquiring a first sound signal through a bone conduction element of the earphone
Data Source
AI summary
An earphone controlling method includes: acquiring a first sound signal through a bone conduction element of the earphone; determining whether the first sound signal includes a voice signal sent by a wearer of the earphone according to the first sound signal; and controlling the earphone to operate in a transparent transmission mode when the first sound signal includes the voice signal.