As well as a number of features designed to make
exploring audio data as revealing as possible, Sonic
Visualiser also has powerful annotation capabilities
to help describe what you find, and the ability to
run automated annotation and analysis plugins.
Features include sophisticated
spectrogram views; multi-resolution waveform and
data displays; manual annotation of time points and
curves; measurement capabilities from spectrogram
and spectrum; playback at any speed; looping and
playback of discontiguous selections; ability to
apply standard audio effects and compare the results
with their inputs; and support for onset detection,
beat tracking, structural segmentation, key
estimation and many other automated feature
extraction algorithms via
Sonic Visualiser contains features
for the following:
Load audio files in WAV, Ogg and MP3
formats, and view their waveforms.
Look at audio visualisations such as
spectrogram views, with interactive adjustment
of display parameters.
Annotate audio data by adding labelled time
points and defining segments, point values and
Overlay annotations on top of one another
with aligned scales, and overlay annotations on
top of waveform or spectrogram views.
View the same data at multiple time
resolutions simultaneously (for close-up and
Run feature-extraction plugins to calculate
annotations automatically, using algorithms such
as beat trackers, pitch detectors and so on.
Import annotation layers from various text
Import note data from MIDI files, view it
alongside other frequency scales, and play it
with the original audio.
Play back the audio plus synthesised
annotations, taking care to synchronise playback
Select areas of interest, optionally
snapping to nearby feature locations, and
audition individual and comparative selections
in seamless loops.
Time-stretch playback, slowing right down or
speeding up to a tiny fraction or huge multiple
of the original speed while retaining a
Export audio regions and annotation layers
to external files.
The design goals for Sonic
To provide the best available core waveform
and spectrogram audio visualisations for use
with substantial files of music audio data.
To facilitate ready comparisons between
different kinds of data, for example by making
it easy to overlay one set of data on another,
or display the same data in more than one way at
the same time.
To be straightforward. The user interface
should be simpler to learn and to explain than
the internal data structures. In this respect,
Sonic Visualiser aims to resemble a consumer
To be responsive, slick, and enjoyable. Even
if you have to wait for your results to be
calculated, you should be able to do something
else with the audio data while you wait. Sonic
Visualiser is pervasively multithreaded, loves
multiprocessor and multicore systems, and can
make good use of fast processors with plenty of
To handle large data sets. The work Sonic
Visualiser does is intrinsically
processor-hungry and (often) memory-hungry, but
the aim is to allow you to work with long audio
files on machines with modest CPU and memory
where reasonable. (Disk space is another matter.
Sonic Visualiser eats that.)