Name
Title | ||
|---|---|---|
Using Context Dependent Distributions For Coding Prediction Residuals Of Companded Audio Signals |
Abstract | ||
|---|---|---|
We propose a context conditioning scheme for encoding the prediction residuals when compressing files containing companded signals. Our scheme encompasses decompanding of the signals, performing linear prediction in the decompanded domain, and then companding back the predicted value into a companded prediction (CP) value, which will differ from the true companded value by an amount called companded prediction residual (CPR). The proposed context conditioning scheme for encoding the CPR, uses a probability distribution conditional on a context made up of two quantities: (1) the predicted value and (2) a scale parameter of the background probability distribution function assumed for the decompanded domain residuals. Various context building schemes and various storing strategies can be used to obtain the necessary conditional coding distribution of the CPR, to be used with an arithmetic coder or range coder. The implementation in fixed point precision can be done very efficiently and with very low memory requirements. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICASSP.2010.5495192 | 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING |
Keywords | Field | DocType |
companding transforms, context modelling, lossless audio compression, G.711 | Speech coding,Pattern recognition,Computer science,Range encoding,Context model,Linear prediction,Probability distribution,Companding,Artificial intelligence,Data compression,Scale parameter | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ioan Tabus | 1 | 276 | 38.23 |
| Florin Ghido | 2 | 35 | 6.97 |
| Adriana Vasilache | 3 | 28 | 5.68 |