SPEECH RECOGNITION BASED ON CONVENTIONAL NEURAL NETWORKS
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Date
2021
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Publisher
СДУ хабаршысы - 2021
Abstract
Abstract. In this research work, the problem of speech recognition is considered in the form of an analysis of the numbers from 1 to 10 recorded by the speaker on the dictaphone. The paper uses the method of recognizing the spectrogram of an audio signal using convolutional neural networks. Also written and implemented an algorithm for processing input data, and an algorithm for recognizing spoken words. In this work, the quality of recognition was assessed for a different number of convolutional layers. A comparison of the recognition quality is made in cases when the input data for the network are the spectrogram of the audio signal or the first two formants extracted from it. The recognition algorithm was tested using examples of male and female voices with different pronunciation lengths.
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Keywords
spectrogram, formant, algorithm for learningneural networks, СДУ хабаршысы - 2021, №2
Citation
D. Almukhametova , D. Kuanyshbay , N. Askar / SPEECH RECOGNITION BASED ON CONVENTIONAL NEURAL NETWORKS / СДУ хабаршысы - 2021