Audio Compression using Munich and Cambridge Filters for Audio Coding with Morlet Wavelet

Article ID

CSTSDE4OZ6E

Audio Compression using Munich and Cambridge Filters for Audio Coding with Morlet Wavelet

S.China Venkateswarlu
S.China Venkateswarlu Adama Science and Technology University
V.Sridhar
V.Sridhar
A.Subba Rami Reddy
A.Subba Rami Reddy
K.Satya Prasad
K.Satya Prasad
DOI

Abstract

The main aim of work is to develop morlet wavelet using Munich and Cambridge filters, for audio compression and most psycho-acoustic models for coding applications use a uniform -equal bandwidth, spectral decomposition for compression. In this paper we present a new design of a psycho-acoustic model for audio coding following the model used in the standard MPEG-1 audio layer 3. This architecture is based on appropriate wavelet packet decomposition instead of a short term Fourier transformation. To fulfill this aim, the following objectives are carried out: Approximate the frequency selectivity of the human auditory system. However, the equal filter properties of the uniform sub- bands do not match the non uniform characteristics of cochlear filters and reduce the precision of psycho-acoustic modeling. This architecture is based on appropriate wavelet packet decomposition instead of a short term Fourier transformation. In this paper Morlet Munich coder shows best performance. The MPEG/Audio is a standard for both transmitting and recording compressed ratio. The MPEG algorithm achieves compression by exploiting the perceptual limitation of the human ear.

Audio Compression using Munich and Cambridge Filters for Audio Coding with Morlet Wavelet

The main aim of work is to develop morlet wavelet using Munich and Cambridge filters, for audio compression and most psycho-acoustic models for coding applications use a uniform -equal bandwidth, spectral decomposition for compression. In this paper we present a new design of a psycho-acoustic model for audio coding following the model used in the standard MPEG-1 audio layer 3. This architecture is based on appropriate wavelet packet decomposition instead of a short term Fourier transformation. To fulfill this aim, the following objectives are carried out: Approximate the frequency selectivity of the human auditory system. However, the equal filter properties of the uniform sub- bands do not match the non uniform characteristics of cochlear filters and reduce the precision of psycho-acoustic modeling. This architecture is based on appropriate wavelet packet decomposition instead of a short term Fourier transformation. In this paper Morlet Munich coder shows best performance. The MPEG/Audio is a standard for both transmitting and recording compressed ratio. The MPEG algorithm achieves compression by exploiting the perceptual limitation of the human ear.

S.China Venkateswarlu
S.China Venkateswarlu Adama Science and Technology University
V.Sridhar
V.Sridhar
A.Subba Rami Reddy
A.Subba Rami Reddy
K.Satya Prasad
K.Satya Prasad

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S.China Venkateswarlu. 1970. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C5): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST Volume 13 Issue C5
Pg. 25- 31
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Audio Compression using Munich and Cambridge Filters for Audio Coding with Morlet Wavelet

S.China Venkateswarlu
S.China Venkateswarlu Adama Science and Technology University
V.Sridhar
V.Sridhar
A.Subba Rami Reddy
A.Subba Rami Reddy
K.Satya Prasad
K.Satya Prasad

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