Sam Perry
140 lines
3.9 KiB
Python
140 lines
3.9 KiB
Python
# Specify analysis parameters for root mean square analysis.
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rms = {
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# Analysis window sizes can be changed for each analysis individually.
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# These do not need to match the grain size of the matcher or synthesis.
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"window_size": 100,
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"overlap": 4,
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}
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f0 = {
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"window_size": 4096,
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"overlap": 4,
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# Currently all frames below this ratio are digaurded and left as silence.
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# Different databases will require different values for the best results.
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# Noisier databases will need lower values than more tonal databases.
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"ratio_threshold": 0.81
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}
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# Specify analysis parameters for variance analysis.
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variance = {
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"window_size": 100,
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"overlap": 4
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}
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# Specify analysis parameters for temporal kurtosis analysis.
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kurtosis = {
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"window_size": 100,
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"overlap": 4
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}
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# Specify analysis parameters for temporal skewness analysis.
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skewness = {
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"window_size": 100,
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"overlap": 4
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}
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# Specify analysis parameters for FFT analysis.
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fft = {
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# The FFT window size determines the window size for all spectral analyses.
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"window_size": 4096
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}
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database = {
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# Enables creation of symbolic links to files not in the database rather
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# than making pysical copies.
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"symlink": True
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}
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# Sets the weighting for each analysis. a higher weighting gives an analysis
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# higher presendence when finding the best matches.
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matcher_weightings = {
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"f0" : 8,
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"spccntr" : 1.,
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"spcsprd" : 1.,
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"spcflux" : 3.,
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"spccf" : 3.,
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"spcflatness": 3.,
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"zerox" : 1.,
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"rms" : 0.1,
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"peak": 0.1,
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"centroid": 0.5,
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"kurtosis": 2.,
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"skewness": 2.,
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"variance": 0.,
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"harm_ratio": 2
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}
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# Specifies the method for averaging analysis frames to create a single value
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# for comparing to other grains. Possible formatters are: 'mean', 'median',
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# 'log2_mean', 'log2_median'
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analysis_dict = {
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# log2_median formats using mel scale. This is useful for analyses such as
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# F0.
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"f0": "median",
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"rms": "mean",
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"zerox": "mean",
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"spccntr": "median",
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"spcsprd": "median",
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"spcflux": "median",
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"spccf": "median",
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"spcflatness": "median",
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"peak": "mean",
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"centroid": "mean",
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"kurtosis": "mean",
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"skewness": "mean",
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"variance": "mean",
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"harm_ratio": "mean"
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}
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analysis = {
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# Force the deletion of any pre-existing analyses to create new ones. This
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# is needed for overwriting old analyses generated with different
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# parameters to the current ones.
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"reanalyse": False
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}
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matcher = {
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# Force the re-matching of analyses
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"rematch": False,
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# This value must be the same as the synthesis grain size to avoid the
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# speeding up or slowing down of the resulting file in relation to the
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# original.
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"grain_size": 100,
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"overlap": 4,
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# Defines the number of matches to keep for synthesis. Note that this must
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# also be specified in the synthesis config
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"match_quantity": 2,
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# Choose the algorithm used to perform matching. kdtree is recommended for
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# larger datasets.
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"method": 'kdtree'
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}
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synthesizer = {
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# Artificially scale the output grain by the difference in RMS values
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# between source and target.
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"enforce_intensity": True,
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# Specify the ratio limit that is the grain can be scaled by.
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"enf_intensity_ratio_limit": 1000.,
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# Artificially modify the pitch by the difference in f0 values between
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# source and target.
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"enforce_f0": True,
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# Specify the ratio limit that is the grain can be modified by.
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"enf_f0_ratio_limit": 1.,
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"grain_size": 100,
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"overlap": 4,
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# Normalize output, avoid clipping of final output by scaling the final
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# frames.
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"normalize" : False,
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# Defines the number of potential grains to choose from matches when
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# synthesizing output.
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"match_quantity": 2
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}
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# Specifies the format for the output file. Changing this has not been tested
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# so may produce errors/undesirable results.
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output_file = {
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"samplerate": 44100,
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"format": 131075,
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"channels": 1
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}
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