pyin is an R package which wraps the pYIN algorithm (Mauch & Dixon, 2014) for fundamental frequency estimation via Sonic Annotator (Cannam, Jewell, Rhodes, Sandler & d’Invernoand, 2010) for use in the R environment.
install.packages("devtools")
devtools::install_github("sebsilas/pyin")library(pyin)
# First test using our test function:
test <- test_pyin()
# If the pyin setup was successful on your system, 'test' should contain a 10x5 data with the transcribed note events of a demo audio file we have distributed with the package.
# Try your own audio file:
my_audio_transcription <- pyin('/my/file/path/audio.wav')
# If you install the itembankr package, you can compute extra melodic features on this:
devtools::install_github('sebsilas/itembankr')
library(dplyr)
library(itembankr)
my_audio_transcription %>% produce_extra_melodic_features()
# where my_audio_transcription contains a pYIN result.
See https://vamp-plugins.org/sonic-annotator/ for information about allowed file types etc.
It is possible to also supply transform files, as described there, via the R package version of pYIN (see the transform_file argument)
This R package currently only supports Windows and Mac 64-bit. If you require support for other systems, please get in touch.
Cannam, C., Jewell, M. O., Rhodes, C., Sandler, M., & d’Inverno, M. (2010). Linked Data And You: Bringing music research software into the Semantic Web. Journal of New Music Research, 39(4), 313–325.
Mauch, M., & Dixon, S. (2014). PYIN: a fundamental frequency estimator using probabilistic threshold distributions. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2014).