Interface to the 'ASSP' Library

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.


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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.

Installation

install.packages("wrassp")
  • or install the latest development version from GitHub (as large parts of wrassp are written in C make sure your system fulfills the requirements for package development (see here)):
library(devtools)
install_github("IPS-LMU/wrassp", build_vignettes = TRUE)

Quick start

  • load the library:
library("wrassp")
  • get path to an audio file:
path2wav <- list.files(system.file("extdata", package = "wrassp"), pattern = glob2rx("*.wav"), full.names = TRUE)[1]
  • calculate formants from audio file:
res=forest(path2wav, toFile=FALSE)
  • plot the first 100 F1 values over time:
plot(res$fm[1:100,1],type='l')
  • for more information see the An introduction to the wraspp package vignette:
vignette('wrassp_intro')

Available signal processing functions

  • 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()
  • dftSpectrum(): Short-term DFT spectral analysis
  • forest(): Formant estimation
  • ksvF0(): F0 analysis of the signal
  • lpsSpectrum(): Linear Predictive smoothed version of dftSpectrum()
  • 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)

Available file handling functions

  • read.AsspDataObj(): read an existing SSFF file into a AsspDataObj which is its in-memory equivalent.
  • write.AsspDataObj(): write a AsspDataObj out to a SSFF file.

For Developers

Checking on rocker/r-devel docker image (prerequisite docker is installed)

  • pull current r-devel image: docker pull rocker/r-devel
  • check if pull worked: docker images
  • check R version in image: docker run rocker/r-devel:latest R --version
  • run interactive version of bash and mount wrassp project folder (==current directory): docker run --rm -ti -v $(pwd):/wrassp rocker/r-devel:latest bash
  • build: RD CMD build --resave-data --no-manual --no-build-vignettes wrassp
  • manually install deps (this might need a bit of tweaking): RD -e 'install.packages(c("stringi","evaluate","compare", "rmarkdown", "knitr", "testthat"))'
  • check: RD CMD check --as-cran wrassp_*.tar.gz

Using rchk for additional checks

  • clone repo git clone https://github.com/joshuaulrich/rchk-docker.git
  • cd rchk-docker
  • build docker image docker build .
  • code below is adapted from final example of this README.md: https://github.com/kalibera/rchk
  • build r package ./bin/R CMD build --resave-data --no-manual --no-build-vignettes /wrassp
  • install package echo 'install.packages("wrassp_0.1.5.tar.gz",repos=NULL)' | ./bin/R --slave
  • run rchk /opt/rchk/scripts/check_package.sh wrassp
  • view rchk results less packages/lib/wrassp/libs/wrassp.so.bcheck and less packages/lib/wrassp/libs/wrassp.so.maacheck

Authors

Raphael Winkelmann

Lasse Bombien

Affiliations

INSTITUTE OF PHONETICS AND SPEECH PROCESSING

News

wrassp 0.1.6

bug fixes

  • fixed rchk issues
  • adressed comments by cran maintainer about description files

wrassp 0.1.5

bug fixes

  • added explicit (void **) type casts for get and put functions
  • increased char array sizes for sprintf to combat compiler warnings of potential buffer overflow

wrassp 0.1.4

new features / performance tweaks / improvements

  • added verbose parameter to sig. proc. functions
  • added new package docs (?wrassp)
  • updated wrassp_intro vignette to include ?wrassp reference
  • improved documentation

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("wrassp")

0.1.6 by Raphael Winkelmann, a month ago


https://github.com/IPS-LMU/wrassp


Report a bug at https://github.com/IPS-LMU/wrassp/issues


Browse source code at https://github.com/cran/wrassp


Authors: Raphael Winkelmann [aut, cre], Lasse Bombien [aut], Michel Scheffers [aut]


Documentation:   PDF Manual  


GPL (>= 3) license


Suggests compare, rmarkdown, knitr, testthat


Imported by emuR.


See at CRAN