Quality Enhancement of Compressed Audio Based on Statistical Conversion

<p/> <p>Most audio compression formats are based on the idea of low bit rate transparent encoding. As these types of audio signals are starting to migrate from portable players with inexpensive headphones to higher quality home audio systems, it is becoming evident that higher bit rates...

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Main Authors: Mouchtaris Athanasios, Cantzos Demetrios, Kyriakakis Chris
Format: Article
Language:English
Published: SpringerOpen 2008-01-01
Series:EURASIP Journal on Audio, Speech, and Music Processing
Online Access:http://asmp.eurasipjournals.com/content/2008/462830
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spelling doaj-9925af21b38e4eb985ee58475978b3072020-11-25T01:12:43ZengSpringerOpenEURASIP Journal on Audio, Speech, and Music Processing1687-47141687-47222008-01-0120081462830Quality Enhancement of Compressed Audio Based on Statistical ConversionMouchtaris AthanasiosCantzos DemetriosKyriakakis Chris<p/> <p>Most audio compression formats are based on the idea of low bit rate transparent encoding. As these types of audio signals are starting to migrate from portable players with inexpensive headphones to higher quality home audio systems, it is becoming evident that higher bit rates may be required to maintain transparency. We propose a novel method that enhances low bit rate encoded audio segments by applying multiband audio resynthesis methods in a postprocessing stage. Our algorithm employs the highly flexible Generalized Gaussian mixture model which offers a more accurate representation of audio features than the Gaussian mixture model. A novel residual conversion technique is applied which proves to significantly improve the enhancement performance without excessive overhead. In addition, both cepstral and residual errors are dramatically decreased by a feature-alignment scheme that employs a sorting transformation. Some improvements regarding the quantization step are also described that enable us to further reduce the algorithm overhead. Signal enhancement examples are presented and the results show that the overhead size incurred by the algorithm is a fraction of the uncompressed signal size. Our results show that the resulting audio quality is comparable to that of a standard perceptual codec operating at approximately the same bit rate.</p>http://asmp.eurasipjournals.com/content/2008/462830
collection DOAJ
language English
format Article
sources DOAJ
author Mouchtaris Athanasios
Cantzos Demetrios
Kyriakakis Chris
spellingShingle Mouchtaris Athanasios
Cantzos Demetrios
Kyriakakis Chris
Quality Enhancement of Compressed Audio Based on Statistical Conversion
EURASIP Journal on Audio, Speech, and Music Processing
author_facet Mouchtaris Athanasios
Cantzos Demetrios
Kyriakakis Chris
author_sort Mouchtaris Athanasios
title Quality Enhancement of Compressed Audio Based on Statistical Conversion
title_short Quality Enhancement of Compressed Audio Based on Statistical Conversion
title_full Quality Enhancement of Compressed Audio Based on Statistical Conversion
title_fullStr Quality Enhancement of Compressed Audio Based on Statistical Conversion
title_full_unstemmed Quality Enhancement of Compressed Audio Based on Statistical Conversion
title_sort quality enhancement of compressed audio based on statistical conversion
publisher SpringerOpen
series EURASIP Journal on Audio, Speech, and Music Processing
issn 1687-4714
1687-4722
publishDate 2008-01-01
description <p/> <p>Most audio compression formats are based on the idea of low bit rate transparent encoding. As these types of audio signals are starting to migrate from portable players with inexpensive headphones to higher quality home audio systems, it is becoming evident that higher bit rates may be required to maintain transparency. We propose a novel method that enhances low bit rate encoded audio segments by applying multiband audio resynthesis methods in a postprocessing stage. Our algorithm employs the highly flexible Generalized Gaussian mixture model which offers a more accurate representation of audio features than the Gaussian mixture model. A novel residual conversion technique is applied which proves to significantly improve the enhancement performance without excessive overhead. In addition, both cepstral and residual errors are dramatically decreased by a feature-alignment scheme that employs a sorting transformation. Some improvements regarding the quantization step are also described that enable us to further reduce the algorithm overhead. Signal enhancement examples are presented and the results show that the overhead size incurred by the algorithm is a fraction of the uncompressed signal size. Our results show that the resulting audio quality is comparable to that of a standard perceptual codec operating at approximately the same bit rate.</p>
url http://asmp.eurasipjournals.com/content/2008/462830
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AT cantzosdemetrios qualityenhancementofcompressedaudiobasedonstatisticalconversion
AT kyriakakischris qualityenhancementofcompressedaudiobasedonstatisticalconversion
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