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2 Journal of Telecommunications and Information Technology

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Manipulation of compressed data using MPEG-7 low level audio descriptors

Lukasiak J., Stirling D., Perrow S., Harders N.

Journal of Telecommunications and Information Technology

2003

nr 2

83-91

This paper analyses the consistency of a set of MPEG-7 low level audio descriptors when the input audio stream has previously been compressed with a lossy compression algorithm. The analysis results show that lossy compression has a detrimental effect on the integrity of practical search and retrieval schemes that utilize the low level audio descriptors. Methods are then proposed to reduce the detrimental effects of compression in searching schemes. These proposed methods include improved searches, switched adaptive scalar and vector prediction, and other prediction schemes based on machine learning principles. Of the proposed schemes the results indicate that searching which incorporates previous and future frames combined with machine learning based prediction best nullifies the effects of compression. However, future scope is identified to further improve the reliability of the MPEG-7 audio descriptors in practical search environments.

Source enhanced linear prediction of speech incorporating simultaneously masked spectral weighting

Lukasiak J., Burnett I.S.

Journal of Telecommunications and Information Technology

2001

nr 3

15-23

Linear prediction is the cornerstone of most modern speech compression algorithms. This paper proposes modifying the calculation of the linear predictor coefficients to incorporate a weighting function based on the simultaneous masking property of the ear. The resultant prediction filter better models the perceptual characteristics of the source and results in the removal of more perceptually important information from the input speech signal than a standard LP filter. When employed in a low rate speech codec the net effect is an improvement in subjective quality, with no increase in transmission rate and only a modest increase in computational complexity.