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Multi-Resolution Speech Spectrogram

by Rohini R. mergu, Dr.Shantanu K. Dixit
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 15 - Number 4
Year of Publication: 2011
Authors: Rohini R. mergu, Dr.Shantanu K. Dixit
10.5120/1937-2587

Rohini R. mergu, Dr.Shantanu K. Dixit . Multi-Resolution Speech Spectrogram. International Journal of Computer Applications. 15, 4 ( February 2011), 28-32. DOI=10.5120/1937-2587

@article{ 10.5120/1937-2587,
author = { Rohini R. mergu, Dr.Shantanu K. Dixit },
title = { Multi-Resolution Speech Spectrogram },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 15 },
number = { 4 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 28-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume15/number4/1937-2587/ },
doi = { 10.5120/1937-2587 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:03:16.186719+05:30
%A Rohini R. mergu
%A Dr.Shantanu K. Dixit
%T Multi-Resolution Speech Spectrogram
%J International Journal of Computer Applications
%@ 0975-8887
%V 15
%N 4
%P 28-32
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An important aid in analysis & display of speech is sound spectrogram. It represents time-frequency-intensity display of short time spectrum. The quality of speech can be studied by visual inspection of spectrogram. This is one of the important applications of spectrogram in speech processing especially in speech enhancement. Another application of spectrogram is in isolating voiced and unvoiced regions. But to conclude from visual inspection the clarity of spectrogram is also important. Before plotting the spectrogram the time domain speech signal is converted to frequency domain. The transform domain used plays vital role in resolution of spectrogram. Generally Fast Fourier Transform is used to convert the time domain signal into frequency domain signal. This paper discusses the effect of using different transform for converting the time domain speech signal into frequency domain before plotting spectrogram. . It is observed that resolution of speech spectrogram is transform dependent.

References
  1. Zenton Goh, Kah-Chye Tan, and B.T.G. Tan,” Postprocessing Method for Suppressing Musical Noise Generated by Spectral Subtraction”, IEEE trans. on Speech and Audio Processing, vol 6, no.3, pgs. 287-292, May 1998.
  2. Richard C. Hendriks, Richard Heusdens ,and Jesper Jensen,” An MMSE Estimator for Speech Enhancement Under A Combined Stochastic–Deterministic Speech Model”, IEEE trans on Speech & Audio Processing,Vol.15,No.2,Feb 2007.
  3. Jesper Jensen and John H.L.Hansen, “Speech Enhancement Using a Constrained Iterative Sinusoidal Model”, IEEE trans. on Speech and Audio Processing, Vol 9, No.7,pgs. 731-740, Oct 2001.
  4. H. Ding, ,I. Y. Soon, S.N.Koh, C.K. Yeo, “A spectral filtering method based on hybrid wiener filters for speech enhancement”, Science Direct, Speech Communication 51(2009) pgs. 259–267
  5. Nicholas W.D. Evans, John S.Mason and Matt J.Roach ,“Noise Compensation using Spectrogram Morphological Filtering”, Speech and Image Research Group, Department of Electrical and Electronic Engineering University of Wales Swansea, UK.
  6. Sharon Gannot, David Burshtein, and Ehud Weinstein,” Iterative and Sequential KalmanFilter-Based Speech Enhancement Algorithms”, IEEE trans on Speech & Audio Processing,Vol.6,No.4,July 1998.
  7. I.Y.Soon, S.N. Koh,“Speech Enhancement Using 2-D Fourier Transform”, IEEE trans. on Speech and Audio Processing, Vol 11, No.6,pgs. 717-724, Nov 2003.
  8. Cyril Plapous, Claude Marro, and Pascal Scalart,” Improved Signal-to-Noise Ratio Estimation For Speech Enhancement”, IEEE trans. on Audio, Speech & Language Processing,Vol.14,No.6,Nov 2006.
Index Terms

Computer Science
Information Sciences

Keywords

Spectrogram Speech Enhancement Speech Processing Speech & Noise Speech Quality SNR Resolution

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