source: doc/aubiopitch.txt @ 8489d7b

feature/autosinkfeature/cnnfeature/cnn_orgfeature/constantqfeature/crepefeature/crepe_orgfeature/pitchshiftfeature/pydocstringsfeature/timestretchfix/ffmpeg5sampleryinfft+
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1NAME
2  aubiopitch - a command line tool to extract musical pitch
3
4SYNOPSIS
5
6  aubiopitch source
7  aubiopitch [[-i] source] [-o sink]
8             [-r rate] [-B win] [-H hop]
9             [-p method] [-u unit] [-l thres]
10             [-T time-format]
11             [-s sil] [-f]
12             [-v] [-h] [-j]
13
14DESCRIPTION
15
16  aubiopitch attempts to detect the pitch, the perceived height of a musical
17  note.
18
19  When started with an input source (-i/--input), the detected pitch are
20  printed on the console, prefixed by a timestamp in seconds. If no pitch
21  candidate is found, the output is 0.
22
23  When started without an input source, or with the jack option (-j/--jack),
24  aubiopitch starts in jack mode.
25
26OPTIONS
27
28  This program follows the usual GNU command line syntax, with long options
29  starting with two dashes (--). A summary of options is included below.
30
31  -i, --input source  Run analysis on this audio file. Most uncompressed and
32  compressed are supported, depending on how aubio was built.
33
34  -o, --output sink  Save results in this file. The file will be created on
35  the model of the input file. The detected frequency is played at the
36  detected loudness.
37
38  -r, --samplerate rate  Fetch the input source, resampled at the given
39  sampling rate. The rate should be specified in Hertz as an integer. If 0,
40  the sampling rate of the original source will be used. Defaults to 0.
41
42  -B, --bufsize win  The size of the buffer to analyze, that is the length
43  of the window used for spectral and temporal computations. Defaults to 2048.
44
45  -H, --hopsize hop  The number of samples between two consecutive analysis.
46  Defaults to 256.
47
48  -p, --pitch method  The pitch detection method to use. See PITCH METHODS
49  below. Defaults to 'default'.
50
51  -u, --pitch-unit unit  The unit to be used to print frequencies. Possible
52  values include midi, bin, cent, and Hz. Defaults to 'Hz'.
53
54  -l, --pitch-tolerance thres  Set the tolerance for the pitch detection
55  algorithm. Typical values range between 0.2 and 0.9. Pitch candidates found
56  with a confidence less than this threshold will not be selected. The higher
57  the threshold, the more confidence in the candidates. Defaults to unset.
58
59  -s, --silence sil  Set the silence threshold, in dB, under which the onset
60  will not be detected. A value of -20.0 would eliminate most onsets but the
61  loudest ones. A value of -90.0 would select all onsets. Defaults to -90.0.
62
63  -T, --timeformat format  Set time format (samples, ms, seconds). Defaults to
64  seconds.
65
66  -m, --mix-input  Mix source signal to the output signal before writing to
67  sink.
68
69  -f, --force-overwrite  Overwrite output file if it already exists.
70
71  -j, --jack  Use Jack input/output. You will need a Jack connection
72  controller to feed aubio some signal and listen to its output.
73
74  -h, --help  Print a short help message and exit.
75
76  -v, --verbose  Be verbose.
77
78PITCH METHODS
79
80  Available methods are:
81
82  default  use the default method
83
84  Currently, the default method is set to yinfft.
85
86  schmitt  Schmitt trigger
87
88  This pitch extraction method implements a Schmitt trigger to estimate the
89  period of a signal. It is computationally very inexpensive, but also very
90  sensitive to noise.
91
92  fcomb  a fast harmonic comb filter
93
94  This pitch extraction method implements a fast harmonic comb filter to
95  determine the fundamental frequency of a harmonic sound.
96
97  mcomb  multiple-comb filter
98
99  This fundamental frequency estimation algorithm implements spectral
100  flattening, multi-comb filtering and peak histogramming.
101
102  specacf  Spectral auto-correlation function
103
104  yin  YIN algorithm
105
106  This algorithm was developed by A. de Cheveigne and H. Kawahara and
107  was first published in:
108
109  De Cheveigné, A., Kawahara, H. (2002) "YIN, a fundamental frequency
110  estimator for speech and music", J. Acoust. Soc. Am. 111, 1917-1930.
111
112  yinfft  Yinfft algorithm
113
114  This algorithm was derived from the YIN algorithm. In this implementation, a
115  Fourier transform is used to compute a tapered square difference function,
116  which allows spectral weighting. Because the difference function is tapered,
117  the selection of the period is simplified.
118
119  Paul Brossier, Automatic annotation of musical audio for interactive systems,
120  Chapter 3, Pitch Analysis, PhD thesis, Centre for Digital music, Queen Mary
121  University of London, London, UK, 2006.
122
123SEE ALSO
124
125  aubioonset(1),
126  aubiotrack(1),
127  aubionotes(1),
128  aubioquiet(1),
129  aubiomfcc(1),
130  and
131  aubiocut(1).
132
133AUTHOR
134
135  This manual page was written by Paul Brossier <piem@aubio.org>. Permission is
136  granted to copy, distribute and/or modify this document under the terms of
137  the GNU General Public License as published by the Free Software Foundation,
138  either version 3 of the License, or (at your option) any later version.
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