Here is the documentation on the ATS analysis parameters:

Appendix I: ATS(Juan Pampin) Analysis Technique Parameters Explanation.
More information on: 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 produce an Analysis Window of 2048 samples to
"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.


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