And in this demonstration class I want to continue what we started in

the last one which was to analyze a sound in that case a sound

of soprano using the short time transform, the topic of this week.

So in this lecture, I want to analyze another sound,

a sound that can give us another view of the short time frame transform.

So let’s open the sound visualizer,

and this is the sound we’re going to analyze today.

This is the sound of a piano and so let's listen that.

[MUSIC]

Okay, so this is a very simple piano phrase, quite clear, five notes.

So let's go directly to the sms-tools and

let's go to the short-time Fourier transform module.

So let's go to the piano sound that is here, piano.wav,

okay now let's decide about the parameters okay?

In the last class we mention that the Blackman was quite a good choice for

what we doing so let's keep it the window size, okay.

This is not a high pitch as the voice, so

we would need quite a bigger window size.

So, I don't know let's start with for example a 1501.

This a knot size window and

this is something that we will whenever possible, we will do.

If we take windows with an odd size,

that means that they can be centered around zero, and

especially for the phase analysis, that's going to be very convenient.

So let's use that and let's take that as a habit of using always odd sized windows.

The FFT has to be bigger than that.

And of course, normally now we will be all using R of 2.

So that is efficient if you use FFT algorithm.

So the power of 2B here then 1,500 is 2,048.

Okay, that's a good size.

And the hop size has to be, for the Blackman window has to be hops,

so that the window overlap correctly.

So, let's say they have to be at least

one-fourth of 1,500, so

that would be around, let's say 325, okay.

That would be around one fourth.

And let's compute.