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added on the 2014-11-12 03:20:04 by algorithm |
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not sure what to think of this (as with the rest of the frodigy series).
might be impressive from a technical point of view (and took a lot of work and brains) but the results are still too far away to be taken seriously.
might be impressive from a technical point of view (and took a lot of work and brains) but the results are still too far away to be taken seriously.
wow.. :) especially love the music on 2nd part! Only thing I would have like to see in this small demo would be the timing it take to play the music...
Thumb for doing it all in a one-filer.
tech
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if this prod is a fake, some info is false or the download link is broken,
do not post about it in the comments, it will get lost.
instead, click here !
Numerous improvements in quality (in particular the addition of more sophisticated frequency analysis)
Overall the demo demonstrates sample playback via using sid waveforms. This has the advantage of using very
minimal cpu time (only a few raster lines) and taking a very small amount of space (around 200 bytes per second packed)
The decoder demonstrates the output of the AWD (Algo Wave Decomposition) which has its plus and minus sides in comparison with the traditional FFT based approach.
+advantages in AWD
Precise frequency/pitch resolution 0-4000hz and up to 16bit frequency range
timbre and harmonic detection with modules for speech, drums and other instrumentation produces higher quality sounds for more complex data in comparison with fft approach due to utilising the c64's 4 waveforms (Pulse wave alone is the equivalent of many sine waves which the fft would decompose)
-disadvantages in AWD
It encodes very slowly
It does not produce optimum data due to local minima issues (although this is somewhat minimised due to different methods of escaping from local minima
For more simple data (speech), quality can suffer
+advantages in the FFT approach
Very fast
produces more optimum quality for more simple sounds and 3 sine outputs.
(and usually sounds smoother for speech)
-disadvantages in the FFT approach
frequency resolution is very low at small time frames. Furthermore due to not being able to utilise the full frequency range (0-22050) for 44100hz samples, it would only use a quarter of the frequencies 0-4000
e.g a 44100hz sample with fft size of 1024 would produce 512 slots with each slot in 43hz intervals (44100/1024)=43. 43*512=approx 22050hz
only the first 93 slots would be in the range 0-4000hz
Solution would be to have a longer chunksize but this would affect transients.
Another alternative would be to pad the large chunksize (which would interpolate values normally giving a better representation of the frequencies
decomposes audio to sine. With the limitation of 3 channels on the c64, this would not give ideal quality for more complex data
There are variants of the FFt which allow finer frequency resolution or non-linear resolution which may work well.