Rsity or at their local health centre. Recording sessions lasted around 40?60 min and included participant interview, cognitive testing and speech recordings. Audio recordings were taken using a portable wave recorder (Edirol R-09HR) and a head-mounted condenser microphone (AKG C-420) spaced about 4 cm from the speaker’s mouth.rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 369:Figure 1. Screenshot of a PRAAT window showing the analysis tiers for the rhythmic analysis. The first window shows the oscillographic signal, and the second window the spectrogram with overlaid F0 (blue, bottom line) and intensity contours (yellow, top line). Underneath are the tiers defined for this particular analysis. The first was a Torin 1 mechanism of action comments tier which was only completed where necessary. The next tier marks the pauses ( p) between utterances, this information was used to calculate the articulation rate. The third tier marks the vowel (v) and consonant (c) boundaries within the signal, which formed the basis of the calculation of the rhythm metrics. The final tier adds an orthographic transcription to these intervals for reference purposes. (Online version in colour.)impact on the results of the rhythm metrics. This was particularly important given the small number of participants investigated in this study. It was ensured that there were no differences in regularity of repetitions between disordered speakers and healthy controls based on the results of the original investigation, and the task was therefore considered appropriate for this study. Measurement parameters for this dataset were based on Liss et al.’s [20] investigation and included the DV, DC, V, nPVI-V, rPVI-C, VarcoV, VarcoC, rPVI-VC and nPVI-VC. Given that Liss et al. [20] had not validated their results perceptually, the full range of metrics was employed in order to establish whether any one of these might be more representative of the disordered performance than others. Calculations of these metrics were performed for five consecutive utterances for each participant, taken from the middle of the repetition sequence. Vowel and consonant intervals were labelled by hand on the spectrographic signal in PRAAT (v. 5.1.32, [35], see figure 1 for a screenshot of a typical analysis window). The final consonant in the utterance (/d/ in `bed’) was excluded from analysis as the release burst was not always visible on the spectrogram. Measurement conventions followed those prescribed for the nPVI-V [19], i.e. adjacent consonants or vowels were labelled as one single C or V interval, and syllabic consonants were labelled as vowels. Once segment boundaries were in place, the interval durations were extracted with a customized PRAAT script. These were subsequently entered into an Excel spreadsheet available from Liss et al. [20] which automatically calculates the various rhythm measures applied in their (and the current) study.1 However, there was one change in procedure fromand thus also of how much they slowed down towards the end of a sentence. In order to exclude the effects of this inter-speaker variability, the rhythm score was calculated separately for each sentence and then averaged to arrive at a single result. This method ARQ-092 chemical information furthermore allowed the researcher to investigate the impact of different articulatory patterns on rhythm metrics across the repetitions.In addition to the rhythm metrics, articulation rate was measured in syllables per second by dividing the number of syllables produced.Rsity or at their local health centre. Recording sessions lasted around 40?60 min and included participant interview, cognitive testing and speech recordings. Audio recordings were taken using a portable wave recorder (Edirol R-09HR) and a head-mounted condenser microphone (AKG C-420) spaced about 4 cm from the speaker’s mouth.rstb.royalsocietypublishing.org Phil. Trans. R. Soc. B 369:Figure 1. Screenshot of a PRAAT window showing the analysis tiers for the rhythmic analysis. The first window shows the oscillographic signal, and the second window the spectrogram with overlaid F0 (blue, bottom line) and intensity contours (yellow, top line). Underneath are the tiers defined for this particular analysis. The first was a comments tier which was only completed where necessary. The next tier marks the pauses ( p) between utterances, this information was used to calculate the articulation rate. The third tier marks the vowel (v) and consonant (c) boundaries within the signal, which formed the basis of the calculation of the rhythm metrics. The final tier adds an orthographic transcription to these intervals for reference purposes. (Online version in colour.)impact on the results of the rhythm metrics. This was particularly important given the small number of participants investigated in this study. It was ensured that there were no differences in regularity of repetitions between disordered speakers and healthy controls based on the results of the original investigation, and the task was therefore considered appropriate for this study. Measurement parameters for this dataset were based on Liss et al.’s [20] investigation and included the DV, DC, V, nPVI-V, rPVI-C, VarcoV, VarcoC, rPVI-VC and nPVI-VC. Given that Liss et al. [20] had not validated their results perceptually, the full range of metrics was employed in order to establish whether any one of these might be more representative of the disordered performance than others. Calculations of these metrics were performed for five consecutive utterances for each participant, taken from the middle of the repetition sequence. Vowel and consonant intervals were labelled by hand on the spectrographic signal in PRAAT (v. 5.1.32, [35], see figure 1 for a screenshot of a typical analysis window). The final consonant in the utterance (/d/ in `bed’) was excluded from analysis as the release burst was not always visible on the spectrogram. Measurement conventions followed those prescribed for the nPVI-V [19], i.e. adjacent consonants or vowels were labelled as one single C or V interval, and syllabic consonants were labelled as vowels. Once segment boundaries were in place, the interval durations were extracted with a customized PRAAT script. These were subsequently entered into an Excel spreadsheet available from Liss et al. [20] which automatically calculates the various rhythm measures applied in their (and the current) study.1 However, there was one change in procedure fromand thus also of how much they slowed down towards the end of a sentence. In order to exclude the effects of this inter-speaker variability, the rhythm score was calculated separately for each sentence and then averaged to arrive at a single result. This method furthermore allowed the researcher to investigate the impact of different articulatory patterns on rhythm metrics across the repetitions.In addition to the rhythm metrics, articulation rate was measured in syllables per second by dividing the number of syllables produced.
