A wrapper around Michel Scheffers's 'libassp' (< http://libassp.sourceforge.net/>). The 'libassp' (Advanced Speech Signal Processor) library aims at providing functionality for handling speech signal files in most common audio formats and for performing analyses common in phonetic science/speech science. This includes the calculation of formants, fundamental frequency, root mean square, auto correlation, a variety of spectral analyses, zero crossing rate, filtering etc. This wrapper provides R with a large subset of 'libassp's signal processing functions and provides them to the user in a (hopefully) user-friendly manner.
wrassp is a wrapper for R around Michel Scheffers's libassp
(Advanced Speech Signal Processor). The libassp library aims at providing functionality for handling speech signal files in most common audio formats and for performing analyses common in phonetic science/speech science. This includes the calculation of formants, fundamental frequency, root mean square, auto correlation, a variety of spectral analyses, zero crossing rate, filtering etc. This wrapper provides R with a large subset of libassp's signal processing functions and provides them to the user in a (hopefully) user-friendly manner.
This package is part of the next iteration of the EMU Speech Database Management System which aims to be as close to an all-in-one solution for generating, manipulating, querying, analyzing and managing speech databases as possible. For an overview of the system please visit this URL: http://ips-lmu.github.io/EMU.html.
wrasspare written in
Cmake sure your system fulfills the requirements for package development (see here)):
library(devtools)install_github("IPS-LMU/wrassp", build_vignettes = TRUE)
path2wav <- list.files(system.file("extdata", package = "wrassp"), pattern = glob2rx("*.wav"), full.names = TRUE)
An introduction to the wraspp packagevignette:
acfana(): Analysis of short-term autocorrelation function
afdiff(): Computes the first difference of the signal
affilter(): Filters the audio signal (see docs for types)
cepstrum(): Short-term cepstral analysis
cssSpectrum(): Cepstral smoothed version of
dftSpectrum(): Short-term DFT spectral analysis
forest(): Formant estimation
ksvF0(): F0 analysis of the signal
lpsSpectrum(): Linear Predictive smoothed version of
mhsF0(): Pitch analysis of the speech signal using Michel's/Modified Harmonic Sieve algorithm
rfcana(): Linear Prediction analysis
rmsana(): Analysis of short-term Root Mean Square amplitude
zcrana(): Analysis of the averages of the short-term positive and negative zero-crossing rates
(see the respective R documentation for more details on all of these functions)
read.AsspDataObj(): read an existing SSFF file into a
AsspDataObjwhich is its in-memory equivalent.
write.AsspDataObj(): write a
AsspDataObjout to a SSFF file.
docker pull rocker/r-devel
docker run rocker/r-devel:latest R --version
docker run --rm -ti -v $(pwd):/wrassp rocker/r-devel:latest bash
RD CMD build --resave-data --no-manual --no-build-vignettes wrassp
RD -e 'install.packages(c("stringi","evaluate","compare", "rmarkdown", "knitr", "testthat"))'
RD CMD check --as-cran wrassp_*.tar.gz
git clone https://github.com/joshuaulrich/rchk-docker.git
docker build .
./bin/R CMD build --resave-data --no-manual --no-build-vignettes /wrassp
echo 'install.packages("wrassp_0.1.5.tar.gz",repos=NULL)' | ./bin/R --slave
sprintfto combat compiler warnings of potential buffer overflow