Recognition of Voice Commands Based on Neural Network Article Swipe

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Speech recognition Computer science Pronunciation Sphinx Artificial neural network Speaker recognition Set (abstract data type) Voice activity detection Time delay neural network Acoustic model Speech processing Artificial intelligence Pattern recognition (psychology) Programming language Linguistics Art Philosophy Visual arts

Vyacheslav Lyashenko , Farah Laariedh , Svitlana Sotnik , M. Ayaz Ahmad ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.18421/tem102-13 · OA: W3167338786

The paper considers features of voice commands pronunciation models, namely, dependence: system accuracy on number of states for phonemes; system accuracy on learning rate; accuracy of system on value of training set. A speech recognition system based on neural networks is proposed. A speech recognition system is not easy to implement and requires an understanding of speech recognition basics. The developed system is compared with Speech Recognition from Google and Pocket Sphinx. The proposed system can recognize voice commands with an accuracy of 84.4 %.