Should Jitter Be Measured by Peak Picking or by Waveform Matching?

the circumstances under which the two methods yield identical or different results. Consider first the sound in figure 1 . This waveform represents a computer-generated [a], created from a perfectly sampled pulse train with a frequency of 117 Hz, filtered with formants at 820, 1,300, 2,300 and 6 higher frequencies. This sound is meant to be representative of what patients are asked to produce in clinical jitter measurement procedures. The short vertical dashed lines indicate the time locations of the underlying pulse train. The tick marks along the bottom of figure 1 indicate the ‘glottal pulses’ as measured by the waveform-matching method. This technique tries to find out at what time distance two consecutive waveshapes look maximally similar. The tick marks along the top of figure 1 indicate the glottal pulses as measured by the peak-picking method, which looks for time locations where the waveform is at its maximum. In the case of the perfectly periodic sound of figure 1 , the two methods give identical results. We can see this because the dotted lines that go up from the tick marks at the bottom exactly touch the tick marks at the top. Also, the figure illustrates that both methods correctly find that all periods, measured as the time distances between consecutive tick marks, are 0.008547 s. Things change when an amount of jitter is applied to the underlying pulse train. Figure 2 shows a sound that is identical to the one in figure 1 , except that the underlying pulse train has an average ‘local jitter’ of 1%. This means that two consecutive underlying periods are on average different by 1%. For instance, the first underlying period (the time distance between the first and second dashed In their article ‘Perturbation measures of voice: a comparative study between Multi-Dimensional Voice Program and Praat’, Maryn et al. [1] make a comparison between the jitter measurements in Praat and the Multi-Dimensional Voice Program (MDVP), and conclude that the two programs give different results. However, the readers of this journal might like to know as well which of the two programs gives the best result. After all, jitter is defined (according to Deliyski’s [2] MDVP manual) as the ‘period-to-period variability of the pitch period’, a definition that suggests that speech sounds possess an underlying ‘true’ jitter that analysis programs could aim to discover. As for which of the two programs provides the better jitter measurements, the authors only give indirect clues. On page 225 they acknowledge (following Boersma [3] ) that the difference between Praat and MDVP is to be ascribed to the methods with which the programs try to determine the time locations of the glottal pulses: Praat’s standard method is ‘waveform matching’, and that of MDVP is ‘peak picking’. As for the quality of the two methods, the authors cite (on page 218) Titze and Liang [4] for finding that the waveform-matching method outperforms the peak-picking method for signals with a jitter below 6% (above 6%, both methods are poor). From this, the reader can indirectly infer that Praat’s method is to be preferred over that of MDVP, but no further explanation is given. The present paper aims at providing the information lacking in the article by Maryn et al. by explaining the exact cause of the difference so that the reader can make up his or her own mind. I will discuss, then, Published online: October 10, 2009