Publication Type:

Conference Proceedings


Proceedings of Symposium of Computer vision and internet (VisionNet), Procedia Computer Science, Volume 58, p.524 - 529 (2015)



Hilbert envelope


Abstract The aim of the proposed work presented in this paper is to determine the speech polarity using the knowledge of epochs and the cosine phase information derived from the complex analytic representation of original speech signal. The work presented in this paper is motivated by the observation of variations in the cosine phase of speech around the Hilbert envelope (HE) peaks according to the polarity changes. As the \{HE\} peaks represent approximate epochs location, the phase analysis is performed by using algorithms which provide better resolution and accuracy of estimated epochs in the present work. In the present work, accurate epochs locations are initially estimated and significant \{HE\} peaks are only selected from the near vicinity of the epochs location for phase analysis. The cosine phase of the speech signal is then computed as the ratio of signal to the \{HE\} of speech. The trend in the cosine phase around the selected significant \{HE\} peaks are observed to be varying according to the speech polarity. The proposed polarity detection algorithm shows better results as compared with the state of the residual skewness based speech polarity detection (RESKEW) method. Thus, the improvement in the polarity detection rates confirms significant polarity information present in the excitation source characteristics around epochs location in speech. The polarity detection rates are also found to be less affected for different levels of noise addition which indicates the effectiveness of the approach against noises. Also, based on the analysis of mean execution time, the proposed polarity detection algorithm is confirmed to be 10 times faster than the \{RESKEW\} algorithm.

Cite this Research Publication

D. Govind, Hisham, P. M., and Pravena, D., “A Robust Algorithm for Speech Polarity Detection Using Epochs and Hilbert Phase Information”, Proceedings of Symposium of Computer vision and internet (VisionNet), Procedia Computer Science, vol. 58. pp. 524 - 529, 2015.