is Ogg Vorbis the best Lossy encoder? (what is?) Options

[snadge]

ive been trying to find out which encoder produces the best audio quality at similar bitrates (say 128k) to other lossy encoders - ive seen a couple of reviews and tests and they seem to point to Ogg Vorbis as being the better encoder - I encoded a WAV file to MP3, AAC, WMA & Vorbis all at 128k CBR and while it was hard to tell any difference the Ogg Vorbis was pumping out higher frequencies at 20Khz + and the rest were up to 18Khz (according to spectrum on Foobar2000)

the only gripe is during conversion Ogg Vorbis was the only one that didnt have the Tag info from the WAV file.

can anyone lead me to more listening test results and the likes so i can ascertain for myself? - i would like others views on "best lossy codec" etc

I read on Wikipedia that AAC at 128k is supposedly Transparent to the lossless source according to listening tests by M-PEG for ITU or something? - I was hoping to adopt AAC as my default rip codec as I have an iPod and MP3 player that plays AAC - but Iam in the market for a new media-player so all this is irrelevant as I can buy something to suite.

thanks in advance for replies

please be gentle...im a noob at all this,

This post has been edited by snadge: Jun 8 2011, 04:17

[[JAZ]]

@Xanikseo: While everything is representable by series of sine waves, only a square wave is representable by a square wave (that is, without applying a filter after that, which makes it more like a sine wave). Only chip music (i.e. music using/emulating old computer audio chips) could potentially benefit from that suggestion.
Let's put another example: If i add to an encoder the possibility to encode the vowels using a model (in fact, that's what speech codecs do), first, i would need deconstruct the sound to separate the speech from the audio, and second, the model may be good for unaltered voice, but in music, that's not necessarily the case.

In the end, lossy encoding is always based on transmiting information about the signal instead of the signal itself. The transformation to sine wave series is just one such way. SBR and Parametric encoding is another way. Modeling (like in speech codecs) is another way. They can be combined, but the more you focus on a specific case, the less applicable it is to other cases (And you would have an increase of cpu, memory and disk usage of the encoder/decoder).


I believe you were trying to say that, to avoid the increase of bitrate needed for complexs parts of the signal, the encoder changed to another way to represent it, so that it could encode that part with fewer bits.
This isn't something new, and in fact it is being done in many encoders. Temporal noise shaping, noise normalization,... those are just some tools used in specific situations to send information about the signal.

In this regard, the best encoder could be the one that could use all the tools available in all circumstances (Like, for example, aplying SBR to a part of the signal without being necesary to use it for all content above a specific frequency band), but that means the stream needs more information to inform when these tools are activated and deactivated, so it is only applicable on the higher end of the bitrate range.
And the truth is that development has focused on the lower end (to add more channels, to be used with video... etc...)

This post has been edited by [JAZ]: Jun 13 2011, 09:48