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Advances in parametric audio coding (1999)
| Venue: | in Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), Mohonk, New Paltz |
| Citations: | 30 - 5 self |
BibTeX
@INPROCEEDINGS{Edler99advancesin,
author = {Bernd Edler and Heiko Purnhagen},
title = {Advances in parametric audio coding},
booktitle = {in Proc. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), Mohonk, New Paltz},
year = {1999},
pages = {31--34}
}
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Abstract
For very low bit rate audio coding applications in mobile communications or on the internet, parametric audio coding has evolved as a technique complementing the more traditional approaches. These are transform codecs originally designed for achieving CDlike quality on one hand, and specialized speech codecs on the other hand. Both of these techniques usually represent the audio signal waveform in a way such that the decoder output signal gives an approximation of the encoder input signal, while taking into account perceptual criteria. Compared to this approach, in parametric audio coding the models of the signal source and of human perception are extended. The source model is now based on the assumption that the audio signal is the sum of “components,” each of which can be approximated by a relatively simple signal model with a small number of parameters. The perception model is based on the assumption that the sound of the decoder output signal should be as similar as possible to that of the encoder input signal. Therefore, the approximation of waveforms is no longer necessary. This approach can lead to a very efficient representation. However, a suitable set of models for signal components, a good decomposition, and a good parameter estimation are all vital for achieving maximum audio quality. We will give an overview on the current status of parametric audio coding developments and demonstrate advantages and challenges of this approach. Finally, we will indicate possible directions of further improvements. 1.
Keyphrases
parametric audio coding speech codecs audio signal current status parametric audio perception model good parameter estimation signal source suitable set human perception encoder input signal simple signal model account perceptual criterion maximum audio quality mobile communication good decomposition possible direction transform codecs demonstrate advantage small number decoder output signal decoder output efficient representation source model signal component audio signal waveform cdlike quality parametric audio coding development traditional approach
