Track short-term DFT power spectrum

Computes a short-term power spectrum via the Fast Fourier Transform using the libassp C library (Scheffers 2012) . Produces an unsmoothed narrow-band spectrum from 0 Hz to the Nyquist rate. Prefer this function when raw spectral detail is needed; use trk_css_spectrum or trk_lps_spectrum for smoothed spectral envelopes.

Usage

trk_dft_spectrum(listOfFiles, beginTime = 0, centerTime = FALSE, endTime = 0, resolution = 40, fftLength = 0, windowShift = 5, window = "BLACKMAN", bandwidth = 0, toFile = FALSE, explicitExt = "dft", outputDirectory = NULL, assertLossless = NULL, logToFile = FALSE, keepConverted = FALSE, convertOverwrites = FALSE, verbose = TRUE)

Arguments

listOfFiles: Character vector of audio file paths. Any format supported by av is accepted; non-native inputs are transcoded automatically.
bandwidth: Numeric. Effective analysis bandwidth in Hz. Default 0 yields the minimum bandwidth determined by the FFT length.
beginTime: Start time for the extracted portion in seconds. Default: NULL (beginning of signal). Note: uses beginTime/endTime (seconds) matching DSP function conventions, unlike read_audio() which uses begin/end.
centerTime: Numeric or logical. Single-frame analysis time point in seconds; overrides beginTime, endTime, and windowShift. Default FALSE.
endTime: The end time of the section of the sound files that should be analysed (in seconds). Use 0 for end of file.
resolution: Numeric. Target FFT frequency resolution in Hz; the FFT length is set to the smallest power-of-2 meeting this target. Default 40.0.
fftLength: Integer. Explicit FFT length in points; overrides resolution. Default 0 (use resolution).
windowShift: Numeric. Frame shift in milliseconds; sets output frame rate (1000 / windowShift Hz). Default 5.0 ms (200 Hz). Must be strictly less than 32 ms (the 512-sample analysis window at 16 kHz). Values other than the training default (5 ms) may slightly reduce accuracy.
window: Character. Analysis window function type. Default "BLACKMAN". See AsspWindowTypes for supported types.
toFile: Logical. If TRUE, write SSFF output files and return the count written. If FALSE, return an AsspDataObj (single file only). Default TRUE.
explicitExt: By default, a character "d" will be prepended to the file name suffix when writing the output to file. The user can also specify an explicit extension which will be used instead.
outputDirectory: The directory where the slice file should be stored. If not defiled (NULL), the sparse slice file will placed in the same folder as the media file.
assertLossless: Character vector of additional file extensions to treat as losslessly encoded.
logToFile: Logical. Write processing log to a file in outputDirectory rather than the console. Default FALSE.
keepConverted: Logical. Retain intermediate transcoded files. Default FALSE.
convertOverwrites: Logical. Allow transcoding to overwrite existing files. Default FALSE.
verbose: Logical. Show a progress bar (sequential path) or a progress-aware parallel apply (pbapply/pbmcapply, if installed).

Value

If toFile = FALSE: an AsspDataObj with track:

DFT[dB]: REAL32, dB power, n_frames x (FFT_length/2 + 1) columns. Power spectral amplitude from 0 Hz to the Nyquist rate.

Frame rate: 1000 / windowShift Hz (default 200 Hz). If toFile = TRUE: integer count of files written, returned invisibly.

Details

The FFT length is determined by resolution unless overridden by fftLength. bandwidth widens the effective analysis window, trading spectral resolution for reduced side-lobe leakage.

References

Scheffers M (2012). “Advanced Speech Signal Processor.” https://sourceforge.net/projects/libassp/files/libassp/.

Author

Raphael Winkelmann

Lasse Bombien

Fredrik Nylén

Examples

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

# calculate dft spectrum
res <- trk_dft_spectrum(path2wav, toFile=FALSE)
#> Applying `method(trk_dft_spectrum, class_character)()` to 1 recording

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