Track spectral tilt using D'Alessandro PeakSlope (Morlet wavelet)

Returns a per-frame spectral tilt estimate related to breathiness and voice quality (Kane and Gobl 2011) . Captures similar information to CPP and H1-H2 but via multi-scale wavelet analysis.

Usage

trk_peakslope(listOfFiles, beginTime = 0, endTime = 0, toFile = FALSE, explicitExt = "psl", outputDirectory = NULL, verbose = TRUE)

Arguments

listOfFiles: Character vector of audio file paths. Any format supported by av is accepted; non-native inputs are transcoded automatically.
toFile: Logical. If TRUE, write SSFF output files and return the paths written invisibly. If FALSE, return an AsspDataObj. Default FALSE.
explicitExt: Character. Output file extension. Default "psl".
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.
endTime: The end time of the section of the sound files that should be analysed (in seconds). Use 0 for end of file.
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.
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:

peakslope: FLOAT, spectral tilt slope (log10(magnitude) per scale unit), n_frames × 1. Negative = energy at low scales (bright/tense voice); positive = energy at high scales (breathy/relaxed voice).

Frame rate: 100 Hz (10 ms hop; 40 ms analysis window). If toFile = TRUE: character vector of output file paths, returned invisibly.

Details

Spectral tilt is estimated by fitting a linear slope across peak magnitudes at seven Morlet wavelet scales. Lower (more negative) values indicate a steeper spectral slope, associated with creakier phonation; higher values indicate breathier or modal phonation.

Seven D'Alessandro Morlet wavelets at octave-spaced scales (2^0 to 2^6) are convolved with the signal. The maximum magnitude in each 40 ms frame is taken per scale, log10-transformed, and a linear regression slope is computed across the seven scale-magnitude pairs.

References

Kane J, Gobl C (2011). “Identifying regions of non-modal phonation using features of the wavelet transform.” In Proceedings of Interspeech 2011, 177–180. doi:10.21437/interspeech.2011-76 . Spectral tilt and energy distribution measures via Morlet wavelet (PeakSlope).

Examples

if (FALSE) { # \dontrun{
# Single file, return object
peakslope <- trk_peakslope("speech.wav", toFile = FALSE)

# Batch process multiple files
files <- c("file1.wav", "file2.wav")
trk_peakslope(files, toFile = TRUE, outputDirectory = "output/")
} # }