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Reseach Article

Effect of Glottal Excitation Interchange in Hindi and Dogri Languages

by Sonika Mahajan, Rajesh Mehra, Parveen K. Lehana
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 9
Year of Publication: 2015
Authors: Sonika Mahajan, Rajesh Mehra, Parveen K. Lehana
10.5120/20361-2563

Sonika Mahajan, Rajesh Mehra, Parveen K. Lehana . Effect of Glottal Excitation Interchange in Hindi and Dogri Languages. International Journal of Computer Applications. 116, 9 ( April 2015), 1-8. DOI=10.5120/20361-2563

@article{ 10.5120/20361-2563,
author = { Sonika Mahajan, Rajesh Mehra, Parveen K. Lehana },
title = { Effect of Glottal Excitation Interchange in Hindi and Dogri Languages },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 9 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number9/20361-2563/ },
doi = { 10.5120/20361-2563 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:36.167989+05:30
%A Sonika Mahajan
%A Rajesh Mehra
%A Parveen K. Lehana
%T Effect of Glottal Excitation Interchange in Hindi and Dogri Languages
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 9
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Voice acoustics is an active area of research which studies speaking voice and has gain popularity due to rapid advancements in digital signal processing. The shape of glottal excitation and the vocal tract may be speaker and language dependent. The objective of this paper is to study the effect of glottal excitation interchange on the quality and intelligibility in Hindi and Dogri languages. For this, recordings of six speakers (3 males and 3 females) were carried out in Dogri and Hindi languages. Cardinal vowels (/a/, /i/, /u/) were extracted from recordings of each speaker. Investigations were carried out by interchanging the glottal excitations corresponding to the vowels in the two languages for each speaker. The analysis of the results showed that interchange of excitation does not provide satisfactory quality of the synthesized speech in terms of identity and clarity of speech. Further, the synthesized speech is perceived as it was spoken in the original language. It was also observed that if any two of the parameters (excitation, gain, vocal tract LPC coefficients) are interchanged, the accent of the original language also changes. It means that minimum two of the three parameters are necessary to interchange for modifying the accent of the language under consideration.

References
  1. Zaher AA. 2009. Recent Advances in signal processing. Publisher In Tech pp. 544.
  2. Tebelskis J. 1995. Speech Recognition using Neural Networks. Ph. D. desertation, Dept School of computer science Carnegie Mellon university Pitts burg,Pennsylvania.
  3. Gold Ben & Morgan. N. 2000. Speech and Audio Signal Processing. Willey, New York.
  4. Joao P. Cabral,Korin Richmond, Junichi Yamagishi and Steve Renals. 2014. Glottal Spectral Separation for Speech Synthesis IEEE Journal, Vol. 8, No. 2, pp. 195-208.
  5. Kawahara,H. ,Masuda-Katsuse,andA. Cheveign'e. 1999. Restructuring speech representations using a pitch –adaptive time- frequency smoothing and an instantaneous-frequency-based F0 Extraction :Possible role of a repetitive structure in sounds Speech Commun. ,vol. 27, no. 3-4, pp. 187-207.
  6. Rulph Chassaing and Donald Reay. 2008. Digital Signal Processing and Applications with C6713 and C6416 DSK, 2ndEdition Wiley Inter Science Pub, London, IEEE PRESS.
  7. Dubey Preeti Pathania Shashi & Devanand. 2011. Comparative study Hindi and Dogri languages with regard to machine translation language in India. Vol. 11, pp. 298-309.
  8. Padmini Rajput & ParveenLehana. 2013. Investigations of the Distributions of Phonemic Durations in Hindi and Dogri. IJNLC Vol. 2, No. 1, pp. 17-30.
  9. Ananthapadmanabha T. V. and B. Yegnarayanana. 1979. Epoch extraction from linear prediction residual for identification of closed glottis interval. IEEE Transactions on Acoustics, Speech, and Signal Processing, 27(4):309-319.
  10. Comeliu Octavian DUMITRU, Inge GAVAT. 2006. A Comparative Study of Feature Extraction Methods Applied to Continuous Speech Recognition in Romanian language. 48thInternational Symposium, Zadar,Croatia.
Index Terms

Computer Science
Information Sciences

Keywords

LPC Component vocal tract parameters glottal source glottal gain