present for s-10 astro guys

69 Hz: Insane Clown Posse - The Tempest - "The Tower"
73 Hz: Evanescence - Fallen - "Imaginary" (at 1:17)
74 Hz: Metallica - Black - "Sad But True"
74 Hz: The Crystal Method - Divided By Night - "Blunts & Robots" (at 1:42)


oh to late we gota cd lol

The_Rowlands wrote:

69 Hz: Insane Clown Posse - The Tempest - "The Tower"
73 Hz: Evanescence - Fallen - "Imaginary" (at 1:17)
74 Hz: Metallica - Black - "Sad But True"
74 Hz: The Crystal Method - Divided By Night - "Blunts & Robots" (at 1:42)


oh to late we gota cd lol

Thanks for the bump! Makes me feel old. That thread was started almost 3 years ago.

I had alot of fun running spectrum analysis on my collection. With all the new dubstep and "random British chap with a keyboard" electronic music, I'm sure there's alot of new songs.

If you have any new songs, I'll update it and bump the thread.

Is there a program to scan multiple songs at a time or are you checking each song one at a time?

Not that I know of. If you're doing enough analysis, I guess a signal processing engineer could write a script, but that's not my trade.

I just put on a good set of headphones and played music while I worked. If the EQ is set to bass heavy, you'll take notice when a good SB song shows up. From there, import it using Audacity and the LameMP3 codec. Highlight the section of interest (then individual beats) and run a Frequency Spectrum Analysis. Set the window type to Hamming and length to as long as possible. Larger window size allows for more fine-grain analysis of low frequency signals (something something, Nyquist frequency).

This will show you the frequency spectrum of those few bars of music. If it maintains a steep peak for more than 30 secs, you have a winner. No song is perfect, but some were very close to it. The current SB CD is pretty good though. I did an analysis here:
Link Potato

Not following what the Nyquist frequency portion of your message meant...
I do see the Analyze->Plot Spectrum mode, and it seems to show peak frequencies - but doesn't seem to indicate the length of the notes...

You choose the length of the highlighted section. The time-domain plot (main squiggly line) will allow you to identify beats pretty easily. Typically I'll look at the individual beat and compare that to the whole section. This gives me an idea of how "tone like" the beat is.

Nyquist frequency refers to the idea that your sampling frequency needs to be twice that of any frequency you're trying to detect. Conversely, when you run a Fourier transform, you need the endpoints of your sample to be 0, and a sufficient amount of data within the window to characterize the frequency of interest. If you're talking about a 1 Hz signal, you'll need to be sampling at atleast 2 Hz to even pick up the signal without aliasing, but to convert the time-domain data into frequency domain (and to pick out the frequency with a narrow peak in the spectrum) you'll need a 50 seconds or longer window. I forget the numbers available, 2000,4000, 8000 etc. Pick the big one.

I've done the pitch shift on a couple different tracks now - and while it does seem to get them to the frequency I want - they sound like garbage... thoughts? I'm using 320kbps mp3s - and exporting as the same...

I can't really describe the sound as distortion - but it sounds the like waveform has definitely been damaged - the bassline sorta of sounds like's been inverted, and doesn't have the fullness of the beat it originally had, like it's being cut off before reaching the full wavelength.

With that high of bitrate, it's odd that you'd see issues.

Digital audio has a sampling rate of 44.1 kHz (usually), to ensure that you can wrap up 20kHz frequencies. The bit rate is just how much information is kept in each sample. Most of us can't hear that high anymore, I'm at 18 kHz for now, so it's a bit of a waste. LINK for hearing test

The pitch shift might be scaling your sampling rate, so I'd try moving to a lossless format. First, I'd just convert MP3 --> WAV, then pitch shift, then export to MP3. If that fails, use a sample rate converter to boost it to 96 kHz. Should prevent any aliasing or saw-toothing.

Not sure it will help, but that's my best guess.

Will try using WAV as intermediate format and try again, thank you for the input.