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Silent voice reconstruction method based on sounding neural potential signal

A nerve potential and signal technology, applied in the field of human-machine interface and artificial intelligence, can solve problems such as low accuracy rate and unclear voice quality

Pending Publication Date: 2022-05-24
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention mainly solves technical problems such as low correct rate of decoding and reconstruction of EEG signals and unclear voice quality existing in the prior art, and provides a high-quality silent voice reconstruction method based on vocal nerve potential signals

Method used

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  • Silent voice reconstruction method based on sounding neural potential signal
  • Silent voice reconstruction method based on sounding neural potential signal
  • Silent voice reconstruction method based on sounding neural potential signal

Examples

Experimental program
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Embodiment

[0061] Embodiment: A silent speech reconstruction system based on neural potential signals in this embodiment, such as figure 1 shown, including:

[0062] Electrode array 101, the electrode array includes at least two electrodes, which are attached to the face to collect neural potential signals related to vocalization;

[0063] The microphone 102 is used to collect speech signals when reading aloud;

[0064] The signal acquisition module 103 amplifies the collected potential signal through the operational amplifier, and sends it to the upper computer through wired or wireless communication, and simultaneously sends the voice signal collected by the microphone to the upper computer through wired or wireless communication when reading aloud ;

[0065] The signal reconstruction module 104 , in the training phase, collects the nerve potential signal when reading aloud and aligns the signal collected by the microphone, performs preprocessing and feature extraction, collects the...

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Abstract

The invention discloses a soundless voice reconstruction method based on a sound production neural potential signal, and the method comprises the steps: collecting a sound production related neural potential signal and a voice signal during sound production through an electrode, and collecting the sound production related neural signal under a soundless condition; moreover, the connection between the silent neural potential signal and the voice signal of the same text is obtained through a deep learning network, the reconstruction of the voice signal under the silent condition, the transmission of the information content under the silent condition and the task of silent information transmission are completed, and the information transmission under the silent condition can be directly carried out. For some occasions where sound cannot be produced, the vocal cord does not vibrate, and the information transmission process is completed in a tacit reading mode.

Description

technical field [0001] The invention relates to the field of human-machine interface and artificial intelligence, in particular to a silent speech reconstruction method based on vocal nerve potential signals, which is used to complete speech reconstruction during silent speech. Background technique [0002] Human-machine interface is a fundamental method to explore human neural activity using hardware and software. Human-machine interfaces allow humans to interact with their surroundings and communicate inner thoughts without the need for words. Silent speech decoding is one of the most popular areas of human interface. Silent speech decoding aims to use biological signals to detect biological activity associated with speech (rather than acoustic data) and decode human thoughts. It has a wide range of real-life applications such as speech rehabilitation, silent operation, as a complement to acoustic speech, etc. [0003] Existing research on silent speech decoding can be ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L25/30G06K9/62G06N3/04G06N3/08
CPCG10L25/30G06N3/084G06N3/048G06N3/045G06F18/241
Inventor 李光王酉李卉艳林皓泓高晗
Owner ZHEJIANG UNIV
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