Improved Autocorrelation-Based Noise Robust Speech Recognition Using Kernel-Based Cross Correlation And Overestimation Parameters

Farahani, Gholamreza; Ahadi, Seyed Mohammad; Homayounpour, Mohammad Mehdi

doi:10.5281/zenodo.40686

2007

DOI: 10.5281/zenodo.40686

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Improved Autocorrelation-Based Noise Robust Speech Recognition Using Kernel-Based Cross Correlation And Overestimation Parameters

Gholamreza Farahani

Seyed Mohammad Ahadi

Mohammad Mehdi Homayounpour

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2016

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Correlation based Transient Removal Method for Speech Signal Enhancement

Tanwar¹,

Somkuwar²

2016

CAE

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In this article, unwanted transients are specified by correlating the previous shade power standards and eliminated the detected transients. Various studies have been done on the autocorrelation based method to perform the noise reduction in speech signals. The speech signal is a one dimensional signal, for that the correlation may be with its delayed function. The proposed method uses recursive approach and the autocorrelation coefficient as a constraint or stopping criterion. The algorithm solves the transient problem of threshold for transient reduction and provides the alternative. The final simulation modelling shows the results.

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Correlation based Transient Removal Method for Speech Signal Enhancement

Tanwar¹,

Somkuwar²

2016

CAE

View full text Add to dashboard Cite

show abstract

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Improved Autocorrelation-Based Noise Robust Speech Recognition Using Kernel-Based Cross Correlation And Overestimation Parameters

Cited by 1 publication

References 11 publications

Correlation based Transient Removal Method for Speech Signal Enhancement

Correlation based Transient Removal Method for Speech Signal Enhancement

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