Re : [MP3 ENCODER] spreading function buggy?

[Lionel Bonnet]

Title: Re : [MP3 ENCODER] spreading function buggy?

> When you say using -10 and 25 gives nonsense, I think you are > confusing tempx and tempy?  The values of -10 and 25 should be applied > to tempy not tempx, as shown above.  They give very reasonable results > which agree with the curve in the Painter article: (taking x=0) > > > Better than the layer 3 results, but the give much more spreading > then is justified by the Painter article. > > > i still don't agree.:-) The curb of the spreading function you mentioned(Figure 9b I suppose) is not for the model II but for the model I (which has a different expression of the spreading function) and is explained page 9, relation 28, : -3 < dz < -1 sf =... -1 < dz < 0 sf =... 0 < dz < 1 sf =... 1< dz < 8 sf = ... (See step 6 of the model I on ISO docs too)You can verify that the curb of the spreading function is linear on each of these intervals. All the discussions of Painter are for model I which he explains page 7.So you can not refer to this curb as a reference. In this case, it's OK the slopes are -10/25 around 0. And it's OK too, i confused tempx and tempy when reading your explanations, but you mustn't have slopes of -10/25for the model II.You can not transform the spreading function of model II in the one of model I : they have completely different  ways of modelling the masking. This time I think Painter made a confusion when quoting the spreading function of model II(relation(4)) with. the slopes of model I(or maybe he didn't check) : he says on page 9 " SF(i,j) approximates the basilar spreading(excitation pattern) described in section II-C" which is false: he probably didn't compare both curbs. My english may not be clear, but think about it. Another point : Painter explains model I, "A non linear Psychoacoustic Model applied to the ISO MPEG Layer 3 coder" from Baumgarte extends model I. It seems that a lot of publications are exploring the model I while we only have the model II for layer III. Did you try to adapt model I to the layer III? With the non-linear addition of masking thresholds, it could have good results too. Lionel