Several functions are available to read audio files into R, including
the readWave()
and readMP3()
functions from
the tuneR
package, as well as tools from the package
av
. SonicScrewdriveR simplifies reading audio files by
providing a single wrapper for these functions,
read_audio()
, which can read audio files in a variety of
formats, including WAV, MP3, and FLAC.
Some existing functions only operate on a single channel at a time.
This may cause unnecessarily complex workflows when bulk analysing files
with different numbers of channels. The allChannels()
function applies a function to each channel and returns a list of
analyses. This technique allows for the same analysis to be performed on
each channel, without reference to the number of channels in the audio
file. Optionally, a cluster can be specified to process channels on
separate processor cores to increase analysis speed.
It is often desirable to process a long audio file in chunks. The
windowing()
function can be used to split an audio file
into overlapping or non-overlapping windows. This function may be
particularly useful for processing long Wave files in a memory-efficient
manner. Optionally, a cluster can be specified to process windows on
separate processor cores to increase processing speed.
The techniques above can be applied to the generic Wave
and WaveMC
objects from the tuneR
package.
The TaggedWave
class extends the Wave
class
from the tuneR
package so that it can include extended
metadata and the results of analyses. This allows for the storage of
additional information about the audio file, such as the location and
time of recording, and the results of analyses. The
tagWave()
function can be used to tag a Wave
or WaveMC
object with additional metadata.
In addition, combined with new classes WaveAugment
,
WaveFilter
, and WaveAnalyse
it is possible to
create a self-documenting pipeline for audio processing and analysis
(that is also compatible with the R pipe).