Synthetic vowels of speakers with Parkinson’s disease and Parkinsonism

Suffix describe type of the file and is separated from the code by underscore. Naming of the files is illustrated on the record HC8a1. The code describes first repetition of the vowel /A/ performed by healthy speaker HC8.

The record HC8a1 consists of following files: HC8a1.wav = waveform of the synthesized replica. This is the reference signal used for the evaluation. Parameters of jitter, shimmer and harmonic to noise ratio (HNR) can be found in dataset.csv.

HC8a1_clean.wav = waveform of the synthesized replica without added noise. We provide this signal to make the model more versatile. Authors may add a different kind of noise to this signal or manipulate with HNR.

Note that that both signals required normalization prior to writing into wav-file. Original scaling factor between HC8a1 and HCa1_clean can be determined from total power of signals and reference HNR value. HC8a1_LF.wav = sample of the glottal pulse used for the synthesis.

HC8a2_impulses.csv = list of impulses’ locations in seconds and corresponding amplitudes. The position of pulses was corrected to match with the beginning of glottal pulse, i.e., first sample of the signal HC8a1_LF.wav begins at each of these positions. The jitter and shimmer listed in dataset.csv were are median values.

Jitter and shimmer by other definitions can be calculated from positions and amplitudes of pulses provided by this file. HC8a1_subharmonics.csv = list of subharmonic intervals described by the start time in seconds and end time in seconds. Corresponding index of amplitude modulation expressed as SHR in percent can be found in the table dataset.csv.

When no subharmonic was determined by the supervised parameterization, no file was included for the speaker and SHR in the dataset.csv was set to zero [1]. [1] Note that the supervised detection had lower sensitivity due to senzitivity of pitch trace in PRAAT, so the occurrence of subharmonics in synthesized data is much lower than in the original dataset analyzed by automated segmentation. This is not a problem because subharmonics were synthesized only at the given interval - this illustrates why it is important to detect subharmonics in other way than by pitch.