Stuttered Speech Recognition And Classification Using Enhanced Kamnan Filter And Neural Network

Vaidianathan, B. and Arulselvi, S. and Karthik, B. (2021) Stuttered Speech Recognition And Classification Using Enhanced Kamnan Filter And Neural Network. In: I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India.

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Abstract

Stuttering or stammering assessment is one of the vital factors in speech recognition algorithms. To reconstruct the stuttered speech into spontaneous speech it is necessary to detect and correct the features influencing the speech signal. In this paper the speech signal is processed based on the disturbances created by acoustic effects like pauses and noises made both externally and internally. To eliminate the effects of noise on speech signal an Enhanced Kalman Filter is introduced here and its performance along with various filters are studied and compared based on the parameters like Mean Square Error (MSE), Mean Absolute Error (MAE), SNR ratio, Peak Signal to Noise ratio and Cross correlation. Then based on the extracted features classification of the speech signal is carried out using Convolutional Neural Network (CNN) algorithm of Deep learning technique.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: stuttering enhanced kalman filter mean square error mean absolute error signal to noise ratio convolutional neural network
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 21 Jun 2021 08:08
Last Modified: 21 Jun 2021 08:08
URI: https://eprints.eudl.eu/id/eprint/3849

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