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Báo cáo hóa học: " Research Article Quality Enhancement of Compressed Audio Based on Statistical Conversion"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Quality Enhancement of Compressed Audio Based on Statistical Conversion | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2008 Article ID 462830 15 pages doi 10.1155 2008 462830 Research Article Quality Enhancement of Compressed Audio Based on Statistical Conversion Demetrios Cantzos 1 2 Athanasios Mouchtaris 3 4 and Chris Kyriakakis1 2 1 Integrated Media Systems Center IMSC University of Southern California Los Angeles CA 90089 USA 2 Ming Hsieh Department of Electrical Engineering University of Southern California Los Angeles CA 90089 USA 3 Institute of Computer Science Foundation for Research and Technology-Hellas FORTH-ICS Heraklion Crete 70013 Greece 4 Department of Computer Science University of Crete Heraklion Crete 71409 Greece Correspondence should be addressed to Demetrios Cantzos cantzos@usc.edu Received 9 October 2007 Revised 17 February 2008 Accepted 20 May 2008 Recommended by Q.-J. Fu 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 featurealignment 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 .