Version:	1.0.5
Date:	2024-01-09
Title:	Interface to the 'ASSP' Library
Description:	A wrapper around Michel Scheffers's 'libassp' (https://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.
Depends:	R (≥ 3.1.1), tibble(≥ 2.1.0)
VignetteBuilder:	knitr
Suggests:	compare(≥ 0.2.4), rmarkdown, knitr, testthat(≥ 0.7.1)
License:	GPL (≥ 3)
URL:	https://github.com/IPS-LMU/wrassp
BugReports:	https://github.com/IPS-LMU/wrassp/issues
RoxygenNote:	7.2.3
NeedsCompilation:	yes
Packaged:	2024-01-09 17:56:10 UTC; markus
Author:	Raphael Winkelmann [aut], Lasse Bombien [aut], Michel Scheffers [aut], Markus Jochim [cre, aut]
Maintainer:	Markus Jochim <markusjochim@phonetik.uni-muenchen.de>
Repository:	CRAN
Date/Publication:	2024-01-09 23:30:02 UTC

wrassp - Interface to the ASSP Library

Description

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.

Details

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.

Available signal processing functions:

1. acfana: Analysis of short-term autocorrelation function

2. afdiff: Computes the first difference of the signal

3. affilter: Filters the audio signal (see docs for types)

4. cepstrum: Short-term cepstral analysis

5. cssSpectrum: Cepstral smoothed version of dftSpectrum

6. dftSpectrum: Short-term DFT spectral analysis

7. forest: Formant estimation

8. ksvF0: F0 analysis of the signal

9. lpsSpectrum: Linear Predictive smoothed version of dftSpectrum

10. mhsF0: Pitch analysis of the speech signal using Michel's (M)odified (H)armonic (S)ieve algorithm

11. rfcana: Linear Prediction analysis

12. rmsana: Analysis of short-term Root Mean Square amplitude

13. zcrana: Analysis of the averages of the short-term positive and negative zero-crossing rates

Available file handling functions:

1. read.AsspDataObj: read an existing SSFF file into a AsspDataObj which is its in-memory equivalent.

2. write.AsspDataObj: write a AsspDataObj out to a SSFF file.

Get/set data format of an AsspDataObj

Description

Function to get or set the data format of an AsspDataObj.

Usage

AsspDataFormat(x)

AsspDataFormat(x)  <- value

Arguments

Details

libassp can store data in binary and ASCII format. This function enables the user to determine the data format of an object read from file and to set it for subsequent writing. Valid values are 'ascii' (or 1) for ASCII format or 'binary' (or 2) for binary IO. Use is discouraged unless the user knows what they are doing.

Value

a string representing the current data format

for AsspDataFormat<-, the updated object

Author(s)

Lasse Bombien

See Also

AsspFileFormat

Get and set AsspFileFormat

Description

Function to get or set the file format of an AsspDataObj.

Usage

AsspFileFormat(x)

AsspFileFormat(x)  <- value

Arguments

Details

libassp handles a number of file formats common in speech research. This function enables the user to determine the file format of an object read from file and to set it for subsequent writing. This allows for file format conversion to some degree. Note, that many conversions are not reasonable/possible: conversions are therefore discouraged unless the user knows what they are doing. Format specifiers can be found in AsspFileFormats and exist in two forms: a code name and a code number. Both are suitable for setting the format.

Value

for AsspFileFormat the code name of the object's currently set file format

for AsspFileFormat<-, the updated object

Author(s)

Lasse Bombien

See Also

AsspFileFormats, AsspDataFormat

Examples

## Not run: 
obj  <- read.AsspDataObj('/path/to/file.wav')
AsspFileFormat(obj)
AsspFileFormat(obj) <- 'SSFF' ## or
AsspFileFormat(obj) <- 20

## End(Not run)

list of possibly useful file formats for AsspDataObj corresponding to the first element of the fileInfo attribute

Description

list of possibly useful file formats for AsspDataObj corresponding to the first element of the fileInfo attribute

Usage

AsspFileFormats

Format

Author(s)

Lasse Bombien

See Also

AsspFileFormat

AsspLpTypes

Description

returns all valid AsspLpTypes according to the assp library

Usage

AsspLpTypes()

Details

wrapper function for AsspLpTypes of wrassp

Value

vector containing lp types

Author(s)

Raphael Winkelmann

AsspSpectTypes

Description

returns all valid AsspSpectTypes according to the assp library

Usage

AsspSpectTypes()

Details

wrapper function for AsspSpectTypes of wrassp

Value

vector containing spectrogram types

Author(s)

Raphael Winkelmann

AsspWindowTypes

Description

returns all valid AsspWindowTypes according to the assp library

Usage

AsspWindowTypes()

Details

wrapper function for AsspWindowTypes of wrassp

Value

vector containing window types

Author(s)

Raphael Winkelmann

acfana

Description

acfana function adapted from libassp

Usage

acfana(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  windowShift = 5,
  windowSize = 20,
  effectiveLength = TRUE,
  window = "BLACKMAN",
  analysisOrder = 0,
  energyNormalization = FALSE,
  lengthNormalization = FALSE,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Analysis of short-term autocorrelation function of the signals in <listOFFiles>. Analysis results will be written to a file with the base name of the input file and extension '.acf'. Default output is in SSFF binary format (track 'acf').

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate short-term autocorrelation
res <- acfana(path2wav, toFile=FALSE)

# plot short-term autocorrelation values
matplot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) + 
        attr(res, 'startTime'), 
        res$acf, 
        type='l', 
        xlab='time (s)', 
        ylab='short-term autocorrelation values')
        

Add a track to an AsspDataObj

Description

Add a track to an AsspDataObj

Usage

addTrack(dobj, trackname, data, format = "INT16", deleteExisting = FALSE)

Arguments

Details

The specified data object is extended by a new track named trackname. If there already is a track with the same name and deleteExisiting is FALSE the function does nothing but returns with an error. If deleteExisting is TRUE the existing track will be removed (see delTrack. data to be added is a numeric matrix (or will be coerced to one). It must have the same number of rows as the tracks that already exist in the object (if any). TODO add format information.

Value

the object including the new track

Author(s)

Lasse Bombien

See Also

delTrack

afdiff

Description

afdiff function adapted from libassp

Usage

afdiff(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  computeBackwardDifference = FALSE,
  computeCentralDifference = FALSE,
  channel = 1,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Computes the first difference of the signal in the audio- formatted file(s) <listOfFiles>. The differentiated signal will be written to a file with the base name of the input file and an extension consisting of '.d', followed by the extension of the input file. The format of the output file will be the same as that of the input file. Differentiation can improve results on F0 analysis of e.g. EGG signals because it removes a DC offset, attenuates very low frequency components - and in the case of central differentiation also very high ones - and enhances the moment of glottal closure.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# compute the first forward difference of the signal
res <- afdiff(path2wav, toFile=FALSE)

# plot samples
# (only plot every 10th element to accelerate plotting)
plot(seq(0,numRecs.AsspDataObj(res) - 1, 10) / rate.AsspDataObj(res), 
     res$audio[c(TRUE, rep(FALSE,9))], 
     type='l', 
     xlab='time (s)', 
     ylab='Audio samples')
     

affilter

Description

affilter function adapted from libassp

Usage

affilter(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  highPass = 4000,
  lowPass = 0,
  stopBand = 96,
  transition = 250,
  useIIR = FALSE,
  numIIRsections = 4,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Filters the audio signal in <listOfFiles>. By specifying the high-pass and/or low-pass cut-off frequency one of four filter characteristics may be selected as shown in the table below.

Please note: per default a high-pass filter from 0 to 4000 Hz is applied.

The Kaiser-window design method is used to compute the coefficients of a linear-phase FIR filter with unity gain in the pass-band. The cut-off frequencies (-6 dB points) of the filters are in the middle of the transition band. The filtered signal will be written to a file with the base name of the input file and an extension corresponding to the filter characteristic (see table). The format of the output file will be the same as that of the input file.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# band-pass filter signal between 4000 and 5000 Hz
res <- affilter(path2wav, highPass=4000, lowPass=5000, toFile=FALSE)

# plot samples
# (only plot every 10th element to accelerate plotting)
plot(seq(0,numRecs.AsspDataObj(res) - 1, 10) / rate.AsspDataObj(res), 
     res$audio[c(TRUE, rep(FALSE,9))], 
     type='l', 
     xlab='time (s)', 
     ylab='Audio samples')
     

cepstrum

Description

calculate cepstral coefficients using libassp

Usage

cepstrum(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  resolution = 40,
  fftLength = 0,
  windowShift = 5,
  window = "BLACKMAN",
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Short-term cepstral analysis of the signal in <listOfFiles> using the Fast Fourier Transform. The number of coefficients per output record will also equal the FFT length / 2 + 1 (i.e. be non-mirrored). Analysis results will be written to a file with the base name of the input file and as extension '.cep'. Default output is in SSFF format with 'cep' as track name.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

See Also

dftSpectrum, cssSpectrum, lpsSpectrum; all derived from libassp's spectrum function

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calulate cepstrum
res <- cepstrum(path2wav, toFile=FALSE)

# plot cepstral values at midpoint of signal
plot(res$cep[dim(res$cep)[1]/2,], 
     type='l', 
     xlab='cepstral value index', 
     ylab='cepstral value')
     

cssSpectrum

Description

calculate cepstrally smoothed spectrum using libassp

Usage

cssSpectrum(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  resolution = 40,
  fftLength = 0,
  windowShift = 5,
  window = "BLACKMAN",
  numCeps = 0,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Short-term spectral analysis of the signal in <listOfFiles> using the Fast Fourier Transform and cepstral smoothing. Analysis results will be written to a file with the base name of the input file and '.css.' as extension. Default output is in SSFF format with 'css' in lower case as track name.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

See Also

dftSpectrum, lpsSpectrum, cepstrum; all derived from libassp's spectrum function.

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate cepstrally smoothed spectrum
res <- cssSpectrum(path2wav, toFile=FALSE)

# plot spectral values at midpoint of signal
plot(res$css[dim(res$css)[1]/2,], 
     type='l', 
     xlab='spectral value index', 
     ylab='spectral value')
     

Remove track from an AsspDataObj

Description

Remove a track from an AsspDataObj object

Usage

delTrack(dobj, trackname)

Arguments

Value

The object without the track named trackname

Author(s)

Lasse Bombien

dftSpectrum

Description

DFT spectrum function adapted from libassp

Usage

dftSpectrum(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  resolution = 40,
  fftLength = 0,
  windowShift = 5,
  window = "BLACKMAN",
  bandwidth = 0,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Short-term spectral analysis of the signal in <listOfFiles> using the Fast Fourier Transform. The default is to calculate an unsmoothed narrow-band spectrum with the size of the analysis window equal to the length of the FFT. The output from the FFT will be converted to a power spectrum in dB from 0 Hz up to and including the Nyquist rate. Analysis results will be written to a file with the base name of the input file and the spectrum type in lower case as extension (e.g. '.dft'). Default output is in SSFF format with the spectrum type in lower case as track name.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

See Also

cssSpectrum, lpsSpectrum, cepstrum; all derived from libassp's spectrum function.

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate dft spectrum
res <- dftSpectrum(path2wav, toFile=FALSE)

# plot spectral values at midpoint of signal
plot(res$dft[dim(res$dft)[1]/2,], 
     type='l', 
     xlab='spectral value index', 
     ylab='spectral value')
     

Timing information on AsspDataObj

Description

Various information on AsspDataObj

Usage

dur.AsspDataObj(x)

numRecs.AsspDataObj(x)

rate.AsspDataObj(x)

startTime.AsspDataObj(x)

Arguments

Details

Some utility function to retrieve duration, number of records, sample rate and so on.

Value

dur: the duration of the AsspDataObj in ms

numRecs: the number of records stored in the AsspDataObj

rate: the data/sample rate of the AsspDataObj in Hz

startTime: start time of the first sample of the AsspDataObj

Author(s)

Lasse Bombien

forest

Description

forest function adapted from libassp

Usage

forest(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  endTime = 0,
  windowShift = 5,
  windowSize = 20,
  effectiveLength = TRUE,
  nominalF1 = 500,
  gender = "m",
  estimate = FALSE,
  order = 0,
  incrOrder = 0,
  numFormants = 4,
  window = "BLACKMAN",
  preemphasis = -0.8,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Formant estimation of the signal(s) in <listOfFiles>. Raw resonance frequency and bandwidth values are obtained by root-solving of the Linear Prediction polynomial from the autocorrelation method and the Split-Levinson-Algorithm (SLA). Resonances are then classified as formants using the so-called Pisarenko frequencies (by-product of the SLA) and a formant frequency range table derived from the nominal F1 frequency. The latter may have to be increased by about 12% for female voices (see NominalF1 and Gender options). Formant estimates will be written to a file with the base name of the input file and extension '.fms'. Default output is in SSFF binary format (tracks 'fm' and 'bw')

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate formant values
res <- forest(path2wav, toFile=FALSE)

# plot formant values
matplot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) + 
          attr(res, 'startTime'), 
        res$fm, 
        type='l', 
        xlab='time (s)', 
        ylab='Formant frequency (Hz)')

Checks whether x is a valid AsspDataObj

Description

Checks whether x is a valid AsspDataObj

Usage

is.AsspDataObj(x, ...)

Arguments

Value

TRUE or FALSE

Author(s)

Lasse Bombien

isAsspLpType

Description

checks if given string is a valid AsspLpType according to the assp library

Usage

isAsspLpType(lpName = NULL)

Arguments

Value

(BOOL) true if lpName is valid; false otherwise

Author(s)

Raphael Winkelmann

isAsspSpectType

Description

checks if given string is a valid AsspSpectType according to the assp library

Usage

isAsspSpectType(spectName = NULL)

Arguments

Value

(BOOL) true if spectName is valid; false otherwise

Author(s)

Raphael Winkelmann

isAsspWindowType

Description

checks if given string is a valid AsspWindowType according to the assp library

Usage

isAsspWindowType(windowName = NULL)

Arguments

Value

(BOOL) true if windowName is valid; false otherwise

Author(s)

Raphael Winkelmann

ksvF0

Description

ksvF0 function adapted from libassp

Usage

ksvF0(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  endTime = 0,
  windowShift = 5,
  gender = "u",
  maxF = 600,
  minF = 50,
  minAmp = 50,
  maxZCR = 3000,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

F0 analysis of the signal in <listOfFiles> using the K. Schaefer-Vincent periodicity detection algorithm. Analysis results will be written to a file with the base name of the input file and extension '.f0'. Default output is in SSFF binary format (track 'F0'). Optionally, location and type of the signal extrema on which the F0 data are based, may be stored in a label file. The name of this file will consist of the base name of the F0 file and the extension '.prd'.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

References

Schaefer-Vincent K (1983) Pitch period detection and chaining: method and evaluation. Phonetica 1983, Vol 40, pp. 177-202

See Also

mhsF0 for an alternative pitch tracker

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate fundamental frequency contour
res <- ksvF0(path2wav, toFile=FALSE)

# plot the fundamental frequency contour
plot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) +
       attr(res, 'startTime'),
     res$F0, 
     type='l', 
     xlab='time (s)', 
     ylab='F0 frequency (Hz)')
     

lpsSpectrum

Description

Calculate Linear Prediction smoothed spectrum using libassp

Usage

lpsSpectrum(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  resolution = 40,
  fftLength = 0,
  windowSize = 20,
  windowShift = 5,
  window = "BLACKMAN",
  order = 0,
  preemphasis = -0.95,
  deemphasize = TRUE,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Short-term spectral analysis of the signal in <listOfFiles> using the Fast Fourier Transform and linear predictive smoothing. Analysis results will be written to a file with the base name of the input file and the spectrum type in lower case as extension (i.e. '.lps'). Default output is in SSFF format with the spectrum type in lower case as track name.

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

See Also

dftSpectrum, cssSpectrum, cepstrum; all derived from libassp's spectrum function.

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate lps spectrum
res <- lpsSpectrum(path2wav, toFile=FALSE)

# plot spectral values at midpoint of signal
plot(res$lps[dim(res$lps)[1]/2,], 
     type='l', 
     xlab='spectral value index', 
     ylab='spectral value')

mhsF0

Description

mhsF0 function adapted from libassp

Usage

mhsF0(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  windowShift = 5,
  gender = "u",
  maxF = 600,
  minF = 50,
  minAmp = 50,
  minAC1 = 0.25,
  minRMS = 18,
  maxZCR = 3000,
  minProb = 0.52,
  plainSpectrum = FALSE,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Pitch analysis of the speech signal in <listOfFile> using Michel's/Modified Harmonic Sieve algorithm. Analysis results will be written to a file with the base name of the input file and extension '.pit'. Default output is in SSFF binary format (track 'pitch').

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

See Also

ksvF0 for an tracking the fundamental frequency

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate fundamental frequency contour
res <- mhsF0(path2wav, toFile=FALSE)

# plot fundamental frequency contour
plot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) +
       attr(res, 'startTime'),
     res$pitch, 
     type='l', 
     xlab='time (s)', 
     ylab='F0 frequency (Hz)')

Normalise a list of filenames so that they can be passed to a signal processing function

Description

Normalise a list of filenames so that they can be passed to a signal processing function

Usage

prepareFiles(listOfFiles)

Arguments

Value

A normalised list of filenames

Author(s)

Raphael Winkelmann

Examples

#   listOfFiles <- prepareFiles(listOfFiles)

print a summary of an AsspDataObj

Description

Prints an overview of ASSP Data Objects

Usage

## S3 method for class 'AsspDataObj'
print(x, ...)

Arguments

Author(s)

Lasse Bombien

See Also

read.AsspDataObj

read.AsspDataObj from a signal/parameter file

Description

read.AsspDataObj creates an object of class dobj from a signal or parameter file readable by the ASSP Library (WAVE, SSFF, AU, ...)

Usage

read.AsspDataObj(fname, begin = 0, end = 0, samples = FALSE)

Arguments

Value

list object containing file data

Author(s)

Lasse Bombien

rfcana

Description

rfcana function adapted from libassp

Usage

rfcana(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  windowShift = 5,
  windowSize = 20,
  effectiveLength = TRUE,
  window = "BLACKMAN",
  order = 0,
  preemphasis = -0.95,
  lpType = "RFC",
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Linear Prediction analysis of <listOfFiles> using the autocorrelation method and the Durbin recursion. This program calculates the RMS amplitudes of the input and residual signal in dB and, per default, reflection coefficients (see '-t' option). Analysis results will be written to a file with the base name of the input file and the parameter type in lower case as extension (e.g. '.rfc'). Default output is in SSFF binary format (tracks 'rms', 'gain' and the LP type in lower case).

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# perform linear prediction analysis
res <- rfcana(path2wav, toFile=FALSE)

# plot reflection coefficients
matplot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) + 
          attr(res, 'startTime'), 
        res$rfc, 
        type='l', 
        xlab='time (s)', 
        ylab='reflection coefficient values')
        

rmsana

Description

rmsana function adapted from libassp

Usage

rmsana(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  windowShift = 5,
  windowSize = 20,
  effectiveLength = TRUE,
  linear = FALSE,
  window = "HAMMING",
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Analysis of short-term Root Mean Square amplitude of the signal in <listOfFiles>. Per default, the RMS values are expressed in decibel (dB) so that they correspond to the short-term power of the signal. Analysis results will be written to a file with the base name of the input file and extension '.rms'. Default output is in SSFF binary format (track 'rms').

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate rms values
res <- rmsana(path2wav, toFile=FALSE)

# plot rms values
plot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) +
       attr(res, 'startTime'),
     res$rms, 
     type='l', 
     xlab='time (s)', 
     ylab='RMS energy (dB)')

tracks.AsspDataObj

Description

List the tracks of an AsspDataObj

Usage

tracks.AsspDataObj(x)

Arguments

Details

AsspDataObj contain tracks (at least one). This function lists the names of these tracks. This function is equivalent to calling names(x).

Value

a character vector containing the names of the tracks

Author(s)

Lasse Bombien

package variable to force the usage of the logger set to FALSE by default

Description

package variable to force the usage of the logger set to FALSE by default

Usage

useWrasspLogger

Format

An object of class logical of length 1.

Author(s)

Raphael Winkelmann

wrassp.logger

Description

Designated logger for the wrassp signal processing functions

Usage

wrassp.logger(fName, fOpts, optLogFilePath, listOfFiles)

Arguments

Details

Function logs the call to a signal processing function (spf) of wrassp. It is called by default if the forceToLog option of the spf is not set to false. I tries to format the output in an easily readable fashion.

Author(s)

Raphael Winkelmann

See Also

match.call

list of default output extensions, track names and output type for each signal processing function in wrassp

Description

list of default output extensions, track names and output type for each signal processing function in wrassp

Usage

wrasspOutputInfos

Format

An object of class list of length 13.

Author(s)

Raphael Winkelmann

write.AsspDataObj to file

Description

Writes an object of class AsspDataObj to a file given the meta information contained in the object.

Usage

write.AsspDataObj(dobj, file = attr(dobj, "filePath"))

Arguments

Author(s)

Lasse Bombien

zcrana

Description

zcrana function adapted from libassp

Usage

zcrana(
  listOfFiles = NULL,
  optLogFilePath = NULL,
  beginTime = 0,
  centerTime = FALSE,
  endTime = 0,
  windowShift = 5,
  windowSize = 25,
  toFile = TRUE,
  explicitExt = NULL,
  outputDirectory = NULL,
  forceToLog = useWrasspLogger,
  verbose = TRUE
)

Arguments

Details

Analysis of the averages of the short-term positive and negative zero-crossing rates of the signal in <listOfFiles>. Analysis results will be written to a file with the base name of the input file and extension '.zcr'. Default output is in SSFF binary format (track 'zcr').

Value

nrOfProcessedFiles or if only one file to process return AsspDataObj of that file

Author(s)

Raphael Winkelmann

Lasse Bombien

Examples

# get path to audio file
path2wav <- list.files(system.file("extdata", package = "wrassp"), 
                       pattern = glob2rx("*.wav"), 
                       full.names = TRUE)[1]

# calculate zcr values
res <- zcrana(path2wav, toFile=FALSE)

# plot zcr values
plot(seq(0,numRecs.AsspDataObj(res) - 1) / rate.AsspDataObj(res) +
       attr(res, 'startTime'),
     res$zcr, 
     type='l', 
     xlab='time (s)', 
     ylab='ZCR values')