Last post by chamill -
^ Thanks for replying to me. I will have to double-check that when I get home later tonight and I'll post on here.

The CD drive finishes completely and my Hard Disk Lights stop blinking. So it's as though it's 100% complete but I don't get the 100% complete indicator.

I'll see if that changes with the over read setting.

Last post by polemon -
Yes, in terms of waveforms signals in the time domain are one dimensional.

If you think of a discrete-time signal - which I assume you're more familiar with - for each sample in a stream of samples, each one has a value. So, your projection function is s(x) -> y, where s(x) is your sample list, x the sample, and y the sample value at point x.

A two-dimensional plot of a function like this. i.e. mapping y for every x, is a mapping. Mappings may or may not produce additional "dimensions" for perception's sake.

If you think of an image, you're thinking of a matrix of values, each corresponding to a pixel (discussing this in terms of bitmaps is a bit easier, here). So, each column (we'll call that x) and each row (we'll call that y), maps to a color (let's call that z).

Assuming we have a grayscale picture, you can map each (x,y) point in that matrix to its pixel value as brightness, giving you that image. However you might think of it as a contour plot, mapping each value of each (x,y) point on axis z, that would result in a 3-dimensional plot. Both are valid, however depending on how we understand the mapping, he might get an image in one instance, or a 3-dimensional plot in another.

Now, let's take a step back from discrete-time signals. I'm assuming you're familiar with the sinusoidal function sin(x). now, let's define a function, which is quite simply: f(x) = sin(x). Now, as we can see from the function definition and the function signature, that it takes only one variable, in this case x. The return value of f(x), we might call y, giving us: y = sin(x). We can now plot this function on a 2D plane, but notice what we're doing here: we're plotting the input and output values of a one-dimensional function onto a 2d plane!

A two-dimensional function might look like this: f(x,y) = sin(x) * y. If we want we can assign the return value of f(x,y) to z, we can think of x, y, and z as coordinates in a 3D plot, however, that depends on how we want to map that function. It is important to note, that both our first and this second example, the function map to a scalar value, however this is not always necessarily a requirement.

Things like FFT, returns a two-dimensional number for each set of input numbers.

Harking back to the one-dimensional-ness of a discrete-time signal, like PCM, we can think of the entire audio file or whatever, as a string of values, like a list. Each item in that list can be addressed by only one coordinate: it's time index. Say our audio chunk is one hundred samples long, and lets call that list 's'. Now, let's use some list/array notation here, so with something like s{x} I can get the value of s at position x. To plot each value, we might say: y = s{x}, so each point x in s is returned and plotted on the y axis. Note, that we're not addressing that point with x and y, y is merely the result or value at position x! Instead we address the value of y ONLY with x! Furthermore (the f(x) = sin(x) being a good example here), note that for each input of x, we get a defined and single result. However, the result would return an array of values if we'd try to map in reverse!

If you have further questions, feel free to ask further questions.

Any representation of data which consists of 2 coordinates for each data point is 2-dimensional. In order to uniquely specify a point, you must give 2 coordinates or there would be confusion.

Incorrect. Case in point: f(x) = sin(x) You're confusing coordinate and return value. The return value is defined by its coordinate, which in case of a simple sinusoid, is only one-dimensional. You can map input coordinates and its return values onto a 2D plane, sure, but this doesn't make the function two-dimensional.

A signal waveform must have 2 coordinates, or else the numerous times a signal has the same amplitude would be indistinguishable from one another.

Incorrect. Case in point: f(x) = sin(x) Periodic functions like sinusoids, are perfectly fine having the same return value every 2π. While the function has periodically the same return value, doesn't mean the signal or whatever other function is invalid. In case of continuous-time domain signals, this is pretty much the only way this actually works. However even lower order functions express this behaviour: f(x) = x², returns 2 for both x = 2 and x = -2. Yet, we can trivially plot these functions on a 2D plane.

A 1-dimensional data representation would have only the single number to unambiguously specify each point. One example of this would be the x- or y-coordinate axis by itself. A 1-dimensional representation of data is almost useless by itself; it only becomes useful when used as a reference for another data set (value on a number line). Once it is referenced to 2 other data sets (such as the x and y coordinates of a signal existing in time) it is then a 2-dimensional data set.

Incorrect. Another simple way of thinking of 1-dimensional structures is strings: Let's define the string S = "Hello, World". Let's further assume, that the first value starts with 0. In that case I can access each letter by only one dimension: S{0} = 'H', S{1} = 'e', S{2} = 'l', S{3} = 'l', and so forth. Note that even though S{2} and S{3} have the same return value (both times 'l') this doesn't invalidate the data structure being one-dimensional.

Your math professor friend is either confused, or is confusing you with his explanation.

No, it makes perfect sense, and is pretty much defined in every single school-type math book, like that. I believe the confusion is down to understand mappings and representations, and actual dimensions of a function.

You can also plot a 3D image on a 2D plane (such as your monitor rendering a 3D object in a game), it does work, because we can either use projection (in that case a rendering pipeline), or some other means (like mapping f(x) = x² onto a piece of paper). Drawing a 3D cube on a piece of paper, doesn't make the cube 2D, neither does drawing the function f(x) = x² as y = x² onto a piece of paper two-dimensional.

64 kbps for stereo tracks sound pretty transparent to the source. The main problem with 48 kbps is that it suffers from artifacts in violins and string based music.

Yeah, I just mentioned the whole 96kbps/128kbps/160kbps thing as that's a pretty safe bet for sound quality standards in combination with encoder efficiency to. basically one of those three settings is the sweet spot for most people and are safe to suggest to people. like if someone wanted a quick answer for me I would just tell them to use 96kbps if they favor storage space or 128kbps if they favor sound quality and be done with it.

but with that said, I guess I could say something like this... if you have some concern with sound quality but still are trying to drive the bit rate to a bare minimum then 64kbps is likely your sweet spot, especially given the info you mentioned.

also, like someone around here mentioned not all that long ago.... I would think it's plausible that many would not notice the difference between say a 64kbps Opus file vs a MP3 v5 (130kbps) (which seems to be about the minimum bit rate for MP3 since that's about the equivalent to 96kbps with Opus/AAC) on your typical headphones/speakers mostly because there are no obvious differences in the overall sound on a typical song as when you just listen to the music without comparing it to the lossless source it's easily good enough overall.

Last post by WhistleChips -
Had the same flaky output from foo_out_upnp until I stopped both the foo_upnp Media Server and Media Renderer. May not have needed to do both but at least I'm now able to use Foobar2k to stream shuffled playlists to my receiver with DSP's, Replaygain and Crossfeed engaged. Preferences > Tools > UPnP > Server > Basic Settings

Still touchy about pausing, skipping, etc. but I had it go over four hours last weekend.

Been tweaking the foo_out_upnp settings this past week to see what effect they have: Preferences > Advanced > Playback > UPnP MediaRenderer Output

So far I'm very happy with ripping FLAC files with the latest EAC 1.03. And I'm learning about how Accurate Rip and Cue Tools works. It's great fun.

I'm able to achieve nice error free rips except for 1 annoying point.... I can never achieve Task Completed 100%! It always stops at 99.9%. But the log file and all the other functions complete successfully. Is there any reason why this could be?

Last post by Nichttaub -
Any representation of data which consists of 2 coordinates for each data point is 2-dimensional. In order to uniquely specify a point, you must give 2 coordinates or there would be confusion. A signal waveform must have 2 coordinates, or else the numerous times a signal has the same amplitude would be indistinguishable from one another.

A 1-dimensional data representation would have only the single number to unambiguously specify each point. One example of this would be the x- or y-coordinate axis by itself. A 1-dimensional representation of data is almost useless by itself; it only becomes useful when used as a reference for another data set (value on a number line). Once it is referenced to 2 other data sets (such as the x and y coordinates of a signal existing in time) it is then a 2-dimensional data set.

Your math professor friend is either confused, or is confusing you with his explanation.

An image consists of a matrix of numbers placed on two axis. In my limited understanding, I would assume sound also has at least two axis, one representing time.

If that is your idea of an image, then I would say that a point sound source - or a "point" as a model for an eardrum - would be 0D rather tham 1D ... But rather than claiming "0D", I would say that your model of an "image" might be wrong or at least not in line with your model of soumd. Each point in the image carries a compound of (time-) frequencies. So: if you insist on "time" in a sound waveform, why don't you insist on time in the light waveform?

There are at least two answers to that latter question. 1: In how the human eye projects colour down to a triplet. But that is how humans work, not what is emitted. 2: In that you think that sound changes over time; "music", not just "chord". But then the analogy should be motion picture rather than image.

Last post by decollated -
First, I just want to say thanks for all the excellent work on the program, which I use every day.

Inspired by greynol, I installed the old foo_rgscan.dll file from fb2k 1.1.5 in order to try the original ReplayGain algorithm. I have only used it a short while so far, but I think I may already prefer it to the EBU R128 RG. However, I miss the newer features from the current RG component, like the oversample peak scan and advanced formatting results dialog.

So, would it possible to allow a user choice of which algorithm to use?

Similarly, I was wondering if a choice of dither method could be offered in the file converter. I would love if fb2k allowed a TPDF dither option in addition to the (I think) noise-shaped type it uses now.