CNN Architectures and Feature Extraction Methods for EEG Imaginary Speech Recognition.

ABSTRACT: Speech is a complex mechanism allowing us to communicate our needs, desires and thoughts. In some cases of neural dysfunctions, this ability is highly affected, which makes everyday life activities that require communication a challenge. This paper studies different parameters of an intelligent imaginary speech recognition system to obtain the best performance according to the developed method that can be applied to a low-cost system with limited resources. In developing the system, we used signals from the Kara One database containing recordings acquired for seven phonemes and four words. We used in the feature extraction stage a method based on covariance in the frequency domain that performed better compared to the other time-domain methods. Further, we observed the system performance w

SUBMITTER: Rusnac AL 

PROVIDER: S-EPMC9268757 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature