SYNOPSIS

aubioonset source
aubioonset [[-i] source] [-o sink]
[-r rate] [-B win] [-H hop]
[-O method] [-t thres]
[-s sil] [-m] [-f]
[-j] [-v] [-h]

DESCRIPTION

aubioonset attempts to detect onset times, the beginning of discrete sound events, in audio signals.

When started with an input source (-i/--input), the detected onset times are given on the console, in seconds.

When started without an input source, or with the jack option (-j/--jack), aubioonset starts in jack mode.

OPTIONS

This program follows the usual GNU command line syntax, with long options starting with two dashes (--). A summary of options is included below.

-i, --input source

Run analysis on this audio file. Most uncompressed and compressed are supported, depending on how aubio was built.

-o, --output sink

Save results in this file. The file will be created on the model of the input file. Onset times are marked by a short wood-block like sound.

-r, --samplerate rate

Fetch the input source, resampled at the given sampling rate. The rate should be specified in Hertz as an integer. If 0, the sampling rate of the original source will be used. Defaults to 0.

-B, --bufsize win

The size of the buffer to analyze, that is the length of the window used for spectral and temporal computations. Defaults to 512.

-H, --hopsize hop

The number of samples between two consecutive analysis. Defaults to 256.

-O, --onset method

The onset detection method to use. See ONSET METHODS below. Defaults to 'default'.

-t, --onset-threshold thres

Set the threshold value for the onset peak picking. Typical values are typically within 0.001 and 0.900. Defaults to 0.1. Lower threshold values imply more onsets detected. Try 0.5 in case of over-detections. Defaults to 0.3.

-s, --silence sil

Set the silence threshold, in dB, under which the pitch will not be detected. A value of -20.0 would eliminate most onsets but the loudest ones. A value of -90.0 would select all onsets. Defaults to -90.0.

-m, --mix-input

Mix source signal to the output signal before writing to sink.

-f, --force-overwrite

Overwrite output file if it already exists.

-j, --jack

Use Jack input/output. You will need a Jack connection controller to feed aubio some signal and listen to its output.

-h, --help

Print a short help message and exit.

-v, --verbose

Be verbose.

ONSET METHODS

Available methods are:

default

Default distance, currently hfc

Default: 'default' (currently set to hfc)

energy

Energy based distance

This function calculates the local energy of the input spectral frame.

hfc

High-Frequency content

This method computes the High Frequency Content (HFC) of the input spectral frame. The resulting function is efficient at detecting percussive onsets.

Paul Masri. Computer modeling of Sound for Transformation and Synthesis of Musical Signal. PhD dissertation, University of Bristol, UK, 1996.

complex

Complex domain onset detection function

This function uses information both in frequency and in phase to determine changes in the spectral content that might correspond to musical onsets. It is best suited for complex signals such as polyphonic recordings.

Christopher Duxbury, Mike E. Davies, and Mark B. Sandler.

Complex domain onset detection for musical signals. In Proceedings of the Digital Audio Effects Conference, DAFx-03, pages 90-93, London, UK, 2003.

phase

Phase based onset detection function

This function uses information both in frequency and in phase to determine changes in the spectral content that might correspond to musical onsets. It is best suited for complex signals such as polyphonic recordings.

Juan-Pablo Bello, Mike P. Davies, and Mark B. Sandler.

Phase-based note onset detection for music signals. In Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing, pages 441­444, Hong-Kong, 2003.

specdiff

Spectral difference onset detection function

Jonhatan Foote and Shingo Uchihashi. The beat spectrum: a new approach to rhythm analysis. In IEEE International Conference on Multimedia and Expo (ICME 2001), pages 881­884, Tokyo, Japan, August 2001.

kl

Kulback-Liebler onset detection function

Stephen Hainsworth and Malcom Macleod. Onset detection in music audio signals. In Proceedings of the International Computer Music Conference (ICMC), Singapore, 2003.

mkl

Modified Kulback-Liebler onset detection function

Paul Brossier, ``Automatic annotation of musical audio for interactive systems'', Chapter 2, Temporal segmentation, PhD thesis, Centre for Digital music, Queen Mary University of London, London, UK, 2006.

specflux

Spectral flux

Simon Dixon, Onset Detection Revisited, in ``Proceedings of the 9th International Conference on Digital Audio Effects'' (DAFx-06), Montreal, Canada, 2006.

AUTHOR

This manual page was written by Paul Brossier <[email protected]>. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.