larana: Linear Prediction analysis using autocorrelation the Durbin...

In humlab-speech/superassp: A speech signal processing using various framworks using a wrassp-like interface

Linear Prediction analysis using autocorrelation the Durbin recursion and log area ratio output.

Description

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, and log area ratios using algorithms implmented in libassp \insertCites5hsuperassp. Input signals not in a file format natively supported will be converted before the autocorrelation functions are computed. The conversion process will display warnings about input files that are not in known losslessly encoded formats.

Usage

larana(listOfFiles = NULL, 
  beginTime = 0.0, 
  centerTime = FALSE, 
  endTime = 0.0, 
  windowShift = 5.0, 
  windowSize = 20.0, 
  effectiveLength = TRUE, 
  window = 'BLACKMAN', 
  order = 0, 
  preemphasis = -0.95,
  toFile = TRUE,
  explicitExt=NULL,
  outputDirectory = NULL, 
  assertLossless = NULL, 
  logToFile = FALSE,
  keepConverted=FALSE,
  verbose = TRUE)

Arguments

listOfFiles	vector of file paths to be processed by function
beginTime	the time point (in seconds) of the start of the analysed interval. A NULL or 0 is interpreted as the start of the signal file. If a vector of time points is supplied, the length of that vector needs to correspond with the length of listOfFiles.
centerTime	sets a single-frame analysis time point (in seconds). Overrides beginTime, endTime and windowShift parameters.
endTime	the time point (in seconds) of the end of the analysed interval. A NULL or 0 is interpreted as the end of the signal file. If a vector of time points is supplied, the length of that vector needs to correspond with the length of listOfFiles.
windowShift	the amount of time (in ms) that the analysis window will be shifted between analysis frames
windowSize	the analysis window size (in ms); overrides the effect of the effectiveLength parameter
effectiveLength	make window size effective rather than exact
window	= the analysis window function type ("BLACKMAN" by default). See AsspWindowTypes for a list of supported window types.
analysisOrder	the analysis order. The NULL or 0 sets the analysis order to the sample rate (in kHz) + 3, so that a signal with a 16000 Hz sampling rate will be analysed using an analysisOrder of 19.
preemphasis	= : set pre-emphasis factor to (default: -0.95)
toFile	Should the function write the results to a file, with the (default) file extension (TRUE) or returned as a list of AsspDataObj objects (FALSE)?
explicitExt	the file extension will be used when result files are written (toFile=TRUE), but the file extension can be set to something else using this function argument.
outputDirectory	directory in which output files are stored. Defaults to NULL which means that the result file will be stored in the same directory as the input file.
verbose	display verbose information about processing steps taken, as well as progress bars.
assertLossless	an optional list of file extensions that the user wants to assert contains losslessly encoded signals data.
logToFile	whether to log commands to a separate logfile in the outputDirectory. Logging will otherwise be in the function-specific logging namespace of logger and will be put wherever this namespace is defined to place its output. See logger::log_appender for details.

Details

The results will be will be written to an SSFF formated file with the base name of the input file and extension .lar with tracks RMS[dB],gain[dB],and LAR.

The function is a re-write of the wrassp::rfcana function with log area ratio output, but with media pre-conversion, better checking of preconditions such as the input file existance, structured logging, and the use of a more modern framework for user feedback.

The native file type of this function is "wav" files (in "pcm_s16le" format), SUNs "au", NIST, or CSL formats (kay or NSP extension). Input signal conversion, when needed, is done by libavcodec and the excellent av::av_audio_convert wrapper function

Value

The number of successfully written files (if toFile=TRUE), or a vector of AsspDataObj objects (if toFile=FALSE).

Note

This function is not considered computationally expensive enough to require caching of results if applied to many signals. However, if the number of signals it will be applied to is very large, then caching of results may be warranted.

Author(s)

Raphael Winkelmann

Lasse Bombien

Fredrik Nylén

References

\insertAllCited

See Also

wrassp::rfcana

AsspWindowTypes

av::av_audio_convert

Examples

# get path to audio file
path2wav <- list.files(system.file("samples","sustained", package = "superassp"), pattern = glob2rx("a1.wav"), full.names = TRUE)

# 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$LAR, 
        type='l', 
        xlab='time (s)', 
        ylab='Log area ratios')
        

humlab-speech/superassp documentation built on May 8, 2024, 2:27 p.m.