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Linux 2.6 - man page for atsa (linux section 1)

ATSA(1) 			  The Canonical Csound Reference			  ATSA(1)

NAME
       atsa - Performs ATS analysis on a soundfile. .

DESCRIPTION
       ATS analysis for use with the Csound ATS Resynthesis opcodes.

SYNTAX
	   csound -U atsa [flags] infilename outfilename

INITIALIZATION
       The following flags can be set for atsa (The default values are stated in parenthesis):
	   -b start (0.000000 seconds)
	   -e duration (0.000000 seconds or end)
	   -l lowest frequency (20.000000 Hertz)
	   -H highest frequency (20000.000000 Hertz)
	   -d frequency deviation (0.100000 of partial freq.)
	   -c window cycles (4 cycles)
	   -w window type (type: 1) (Options: 0=BLACKMAN, 1=BLACKMAN_H, 2=HAMMING, 3=VONHANN)
	   -h hop size (0.250000 of window size)
	   -m lowest magnitude (-60.000000)
	   -t track length (3 frames)
	   -s min. segment length (3 frames)
	   -g min. gap length (3 frames)
	   -T SMR threshold (30.000000 dB SPL)
	   -S min. segment SMR (60.000000 dB SPL)
	   -P last peak contribution (0.000000 of last peak's parameters)
	   -M SMR contribution (0.500000)
	   -F File Type (type: 4) (Options: 1=amp.and freq. only,
	     2=amp.,freq. and phase, 3=amp.,freq. and residual,
	     4=amp.,freq.,phase, and residual)

PARAMETERS
       ATS analysis was devised by Juan Pampin. For complete information on ATS visit:
       http://www-ccrma.stanford.edu/~juan/ATS.html.

       Analysis parameters must be carefully tuned for the Analysis Algorithm (ATSA) to properly
       capture the nature of the signal to be analyzed. As there are a significant number of
       them, ATSH offers the possibility of Saving/Loading them in a Binary File carrying the
       extension "*.apf". The extension is not mandatory, but recommended. A brief explanation of
       each Analysis Parameters follows:

	1. Start (secs.): the starting time of the analysis in seconds.

	2. Duration (secs.): the duration time of the analysis in seconds. A zero means the whole
	   duration of the input sound file.

	3. Lowest Frequency (Hz.): this parameter will partially determine the size of the
	   Analysis Window to be used. To compute the size of the Analysis Window, the period of
	   the Lowest Frequency in samples (SR / LF) is multiplied by the number of cycles of it
	   the user wants to fit in the Analysis Window (see parameter 6). This value is rounded
	   to the next power of two to determine the size of the FFT for the analysis. The
	   remaining samples are zero-padded. If the signal is a single, harmonic sound, then the
	   value of the Lowest Frequency should be its fundamental frequency or a sub-harmonic of
	   it. If it is not harmonic, then its lowest significant frequency component may be a
	   good starting value.

	4. Highest Frequency (Hz.): highest frequency to be taken into account for Peak
	   Detection. Once it is determined that no relevant information is found beyond a
	   certain frequency, the analysis may be faster and more accurate setting the Highest
	   Frequency parameter to that value.

	5. Frequency Deviation (Ratio): frequency deviation allowed for each peak in the Peak
	   Continuation Algorithm, as a ratio of the frequency involved. For instance,
	   considering a peak at 440 Hz and a Deviation of .1 will produce that the Peak
	   Continuation Algorithm will only try to find candidates for its continuation between
	   396 and 484 Hz (10% above and below the frequency of the peak). A small value is
	   likely to produce more trajectories whilst a large value will reduce them, but at the
	   cost of rendering information difficult to be further processed.

	6. Number of Cycles of Lowest Frequency to fit in Analysis Window: this will also
	   partially determine the size of the Fourier Analysis Window to be used. See Parameter
	   3. For single harmonic signals, it is supposed to be more than one (typically 4).

	7. Hop Size (Ratio): size of the gap between one Analysis Window and the next expressed
	   as a ratio of the Window Size. For instance, a Hop Size value of .25 will "jump" by
	   512 samples (Windows will overlap for a 75% of their size). This parameter will also
	   determine the size of the analysis frames obtained. Signals that change their spectra
	   very fast (such as Speech sounds) may need a high frame rate in order to properly
	   track their changes.

	8. Amplitude Threshold (dB): the highest amplitude value to be taken into account for
	   Peak Detection.

	9. Window Type: the shape of the smoothing function to be used for the Fourier Analysis.
	   There are four choices available at present: Blackman, Blackman-Harris, Von Hann, and
	   Hanning. Precise specifications about them are easily found on D.S.P. bibliography.

       10. Track Length (Frames): The Peak Continuation Algorithm will "look-back" by Length
	   frames in order to do its job better, preventing frequency trajectories from curving
	   too much and loosing stability. However, a large value for this parameter will slow
	   down the analysis significantly.

       11. Minimal Segment Length (Frames): once the analysis is done, the spectral data can be
	   further "cleaned" up during post-processing. Trajectories shorter than this value are
	   suppressed if their average SMR is below Minimal Segment SMR (see parameters 16 and
	   14). This might help to avoid non-relevant sudden changes while keeping a high frame
	   rate, reducing also the number of intermittent sinusoids during synthesis.

       12. Minimal Gap Length (Frames): as parameter 11, this one is also used to clean up the
	   data during post-processing. In this case, gaps (zero amplitude values, i.e.
	   theoretical "silence") longer than Length frames are filled up with
	   amplitude/frequency values obtained by linear interpolation of the adjacent active
	   frames. This parameter prevents sudden interruptions of stable trajectories while
	   keeping a high frame rate.

       13. SMR Threshold (dB SPL): also a post-processing parameter, the SMR Threshold is used to
	   eliminate partials with low averages.

       14. Minimal Segment SMR (dB SPL): this parameter is used in combination with parameter 11.
	   Short segments with SMR average below this value will be removed during
	   post-processing.

       15. Last Peak Contribution (0 to 1): as explained in Parameter 10, the Peak Continuation
	   Algorithm "looks-back" several number of frames to do its job better. This parameter
	   will help to weight the contribution of the first precedent peak over the others. A
	   zero value means that all precedent peaks (to the size of Parameter 10) are equally
	   taken in account.

       16. SMR Contribution (0 to 1): In addition to the proximity in frequency of the peaks, the
	   ATS Peak Continuation Algorithm may use psycho-acoustic information (the
	   Signal-to-Mask-Ratio, or SMR) to improve the perceptual results. This parameter
	   indicates how much the SMR information is used during tracking. For instance, a value
	   of .5 makes the Peak Continuation Algorithm to use a 50% of SMR information and a 50%
	   of Frequency Proximity information to decide which is the best candidate to continue a
	   sinusoidal track.

EXAMPLES
       The following command:

		     atsa -b0.1 -e1 -l100 -H10000 -w2 audiofile.wav audiofile.ats

       Generates the ATS analysis file 'audiofile.ats' from the original 'audiofile.wav' file. It
       begins analysis from second 0.1 of the file and the analysis is performed for 1 second
       thereafter. The lowest frequency stored is 100 Hz and the highest is 10kHz. A Hamming
       window is used for each analysis frame.

AUTHORS
       Barry Vercoe
       MIT Media Lab

	   Author.

       Dan Ellis
       MIT Media Lab,
		 Cambridge
		 Massachussetts

	   Author.

COPYRIGHT
5.07					    06/23/2009					  ATSA(1)


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