Silent voice decoding method based on surface electromyogram signals
A technology of myoelectric signal and speech decoding, which is applied in the field of accurate and natural silent speech recognition and silent speech decoding, can solve the problems that are difficult to meet the needs of actual speech communication, and achieve excellent phrase recognition accuracy and low decoding word errors rate and reduce the effect of word error rate
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[0075] In this embodiment, a silent speech decoding method based on surface EMG signals, such as figure 1 shown, it includes the following steps:
[0076] Step 1. Construct a silent speech surface EMG dataset D:
[0077] Construct a corpus containing R Chinese phrases E={e 1 ,…,e v ,…,e R }, where e v Represents the vth Chinese phrase in the corpus, all R Chinese phrases are generated by a dictionary containing L different syllables; the surface EMG data of the user's silent pronunciation corpus are collected by flexible high-density electrode arrays and multi-channel signal conversion equipment, Then, the surface EMG signal data is divided into non-overlapping frames, and the time domain features of each frame are extracted respectively, so as to obtain M EMG signal feature samples, which are recorded as the data set D={(x 1 ,y 1 ),(x 2 ,y 2 ),...,(x i ,y i ),...,(x M ,y M )}, where x i represents the i-th EMG signal feature sample, and Represents the i-th EM...
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