Accuracy analysis of single channel speech quality improvement in background noise using empirical wavelet transform comparing with discrete wavelet transform for improved accuracy

The objective is to determine the improvement in the quality of speech recorded in noisy environments by comparing the Empirical Wavelet Transform with the Discrete Wavelet Transform. The data utilized in this experiment was obtained from the open access Kaggle dataset. To determine the appropriate...

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Bibliographic Details
Main Authors: Kumar, J. T., Mariam, M. K. B., Sathish, S., Durumutla, V.
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Algorithms
Background noise
Datasets
Discrete Wavelet Transform
Speech
Wavelet analysis
Wavelet transforms
Online Access:Get full text
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Summary:The objective is to determine the improvement in the quality of speech recorded in noisy environments by comparing the Empirical Wavelet Transform with the Discrete Wavelet Transform. The data utilized in this experiment was obtained from the open access Kaggle dataset. To determine the appropriate sample size for our analysis, we used ClinCalc with an alpha value of 0.05, beta of 0.2, and g power of 0.8. The resulting sample size for each group was 45, for a total of 90 participants. To ensure the correctness of our analysis, we separated our dataset into three subsets: 80% for training, 10% for testing, and 10% for validation. Using the SPSS software, we conducted a performance analysis to compare the effectiveness of various techniques. After conducting a thorough analysis, the Empirical wavelet transform algorithm was found to have accuracy of 82%, while another wavelet algorithm on Discrete transform had an accuracy of 65%. An independent samples T-Test was then performed, and the resulting significance value was p=0.001 (p
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0230516