Throat Vibration to Voice Frequency Conversion via AI Processing
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Solution Overview
Problem
Existing sound collecting devices, particularly those using piezoelectric technology, face challenges in maintaining clarity during user movement or in noisy environments, as they require manual adjustment and can be inconvenient due to swinging microphones, and throat-based devices suffer from small sound volumes and signal type mismatch.
Innovation Solution
A method for converting vibration to voice frequency wirelessly using a computing device with a vibration sensor and voice frequency sensor, employing an AI algorithm like deep neural networks to process and convert vibration data into voice-frequency output signals, utilizing features such as log power spectrum, Mel-frequency cepstrum, or linear predictive coding, to provide clear and stable voice output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If air-conductive sound collecting devices are used, then voice reception is facilitated, but the user needs to hold the device close to the mouth which makes it difficult to spare hands and causes inconvenience during movement
Solution Approach 1:
The patent replaces the mechanical air-conductive microphone system with a vibration-based sensing system. The vibration sensor detects throat vibrations directly, eliminating the need for air-conductive path and manual positioning of the device near the mouth, thus freeing the user's hands while maintaining voice collection capability
Solution Approach 2:
The patent introduces throat vibration as an intermediary between the voice source and the sensing device. Instead of directly capturing air-conducted sound, the system uses throat vibrations as a mediator to transmit voice information to the vibration sensor, enabling hands-free operation while improving stability during movement
2Ease of operation
If throat-vibrating sound collecting devices are used, then hand availability is improved, but unclarity occurs in the collected sound
Solution Approach 1:
The patent employs feedback mechanisms where the collected vibration data is processed and refined through algorithms that compensate for signal degradation. The system continuously adjusts the processing parameters based on the detected vibration patterns to maintain sound clarity while using the convenient throat-based collection method
Solution Approach 2:
The patent applies parameter changes in the signal processing domain, transforming the raw vibration data through various processing parameters and algorithms to enhance clarity. By adjusting processing parameters such as filtering characteristics and transformation methods, the system recovers clear voice signals from the throat vibration source
3Ease of operation
If vibration sound collecting devices are used, then hand availability is improved, but the small throat sound volume leads to unclarity
Solution Approach 1:
The patent applies the anti-weight principle by compensating for the weak throat sound signal through algorithmic enhancement. The processing system counteracts the small signal amplitude by applying gain adjustments and noise reduction techniques, effectively amplifying the useful signal while suppressing background noise and artifacts
4Measurement precision
If the throat sound signal and vibration signal are different signal types, then sensing capability is improved, but their compensation becomes difficult
Solution Approach 1:
The patent transforms vibration signals into voice-frequency signals through parameter changes in the signal processing domain. By applying appropriate transformation parameters and processing algorithms, the system converts the mechanical vibration data into acoustic signal representations, enabling direct comparison and compensation between different signal types
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
This approach enables clear voice output by generating voice-frequency reference data from initial vibration and voice data, allowing for accurate conversion of subsequent vibration data into high-quality voice signals, reducing the need for manual adjustments and improving usability in dynamic environments.
Implementation Method 1
a piezoelectric device that can generate piezoelectric signals according to vibrations is attached to the human body for sensing the vibrations produced when the human body makes sound
Implementation Method 2
Normal sound collecting devices include capacitive and piezoelectric sound collecting devices
Data Source
AI summary
The present application discloses a Method for converting vibration to voice frequency wirelessly and a method thereof. By sensing a first vibration variation data and a voice frequency variation data of a vocal vibration part in a first sensing period, a voice frequency reference data is obtained from the voice frequency variation data and the first vibration result. A second vibration result is obtained at a second sensing period for converting to a voice frequency output signal, and the voice frequency output signal is used to output as a voice signal corresponding to the voice frequency various result. Thus, the present application provides a voice signal close to a human voice.