S, some researchers have proposed to investigate consonantal segments. This is based on the notion that languages differ not only in their vowel duration but also in the structure of the remaining syllable components. For example, stress-timed languages tend to be rich in consonant clusters, whereas syllable-timed languages predominantly include simple consonant-vowel combinations [16]. Currently available consonantal measures include the DC [16], VarcoC [17] and rPVI-C [19] measures. Note that these consonant measures tend not to be rate normalized, as consonant durations vary less across different speaking rates than vowels. Finally, a number of metrics have gone beyond vowels or consonants as their unit of measurement and look at the variability of syllable duration (VarcoVC [20], variability index (VI) [21]) or whole stress groups (ISI [22]) to characterize rhythm. The application of the above metrics in clinical research was based on the fact that some of the differences observed between typical and disordered rhythmic performance appeared to mirror the cross-linguistic distinction between stress- and syllable-timed languages. It thus seemed likelyrstb.royalsocietypublishing.orgconsonant DC [16] VarcoC [17] rPVI-C [19]syllable VarcoVC [20] VI [21]stress group ISI [22]Phil. Trans. R. Soc. B 369:that the measures would be able to identify deviations from normal rhythm and thus act as a diagnostic tool. Furthermore, the fact that cross-linguistic rhythm metrics were able to reflect the continuum between stress and syllable timing suggested their suitability to quantify the extent of deviation from normal rhythmic performance in impaired populations. This feature would be important in terms of judging the severity of the disorder and would allow the metric to function as a therapy outcome measure to indicate potential improvement in performance after treatment. In the attempt to investigate whether rhythm metrics were indeed valid and reliable tools to capture disorders of speech timing, researchers applied a wide range of the above measures. Of these, the PVI was one of the first to be applied to clinical speech [23?5]. Another early attempt involved the application of the ISI to Swedish speakers with dysarthria [26]. These studies order ARRY-470 demonstrated that the measures could successfully differentiate between groups of disordered participants and matched healthy controls. Encouraged by these results, Liss et al. [20] investigated the n-PVI, as well as DV and DC and measures of syllable variability (VarcoVC, nPVI-VC and rPVI-VC) with the aim to assess which were most SCIO-469 solubility suitable to distinguish healthy controls from speakers with dysarthria, as well as different types of dysarthria from each other. They found that variants of the PVI and Varco metrics were particularly successful in discriminating speakers from each other, but that the focus of the comparison determined which of the measures was optimal, i.e. a metric might be better suited to identify speakers with PD than those with ataxia, and in some cases, a combination of predictor variables was most effective to differentiate speaker groups. It is noteworthy that in a subsequent study by Kim et al. [27], the PVI was not successful in distinguishing different types of dysarthric speakers from each other (no results are reported in relation to healthy controls). The authors state that this might have been partly due to the use of the non-normalized version of the PVI, as opposed to the rate-.S, some researchers have proposed to investigate consonantal segments. This is based on the notion that languages differ not only in their vowel duration but also in the structure of the remaining syllable components. For example, stress-timed languages tend to be rich in consonant clusters, whereas syllable-timed languages predominantly include simple consonant-vowel combinations [16]. Currently available consonantal measures include the DC [16], VarcoC [17] and rPVI-C [19] measures. Note that these consonant measures tend not to be rate normalized, as consonant durations vary less across different speaking rates than vowels. Finally, a number of metrics have gone beyond vowels or consonants as their unit of measurement and look at the variability of syllable duration (VarcoVC [20], variability index (VI) [21]) or whole stress groups (ISI [22]) to characterize rhythm. The application of the above metrics in clinical research was based on the fact that some of the differences observed between typical and disordered rhythmic performance appeared to mirror the cross-linguistic distinction between stress- and syllable-timed languages. It thus seemed likelyrstb.royalsocietypublishing.orgconsonant DC [16] VarcoC [17] rPVI-C [19]syllable VarcoVC [20] VI [21]stress group ISI [22]Phil. Trans. R. Soc. B 369:that the measures would be able to identify deviations from normal rhythm and thus act as a diagnostic tool. Furthermore, the fact that cross-linguistic rhythm metrics were able to reflect the continuum between stress and syllable timing suggested their suitability to quantify the extent of deviation from normal rhythmic performance in impaired populations. This feature would be important in terms of judging the severity of the disorder and would allow the metric to function as a therapy outcome measure to indicate potential improvement in performance after treatment. In the attempt to investigate whether rhythm metrics were indeed valid and reliable tools to capture disorders of speech timing, researchers applied a wide range of the above measures. Of these, the PVI was one of the first to be applied to clinical speech [23?5]. Another early attempt involved the application of the ISI to Swedish speakers with dysarthria [26]. These studies demonstrated that the measures could successfully differentiate between groups of disordered participants and matched healthy controls. Encouraged by these results, Liss et al. [20] investigated the n-PVI, as well as DV and DC and measures of syllable variability (VarcoVC, nPVI-VC and rPVI-VC) with the aim to assess which were most suitable to distinguish healthy controls from speakers with dysarthria, as well as different types of dysarthria from each other. They found that variants of the PVI and Varco metrics were particularly successful in discriminating speakers from each other, but that the focus of the comparison determined which of the measures was optimal, i.e. a metric might be better suited to identify speakers with PD than those with ataxia, and in some cases, a combination of predictor variables was most effective to differentiate speaker groups. It is noteworthy that in a subsequent study by Kim et al. [27], the PVI was not successful in distinguishing different types of dysarthric speakers from each other (no results are reported in relation to healthy controls). The authors state that this might have been partly due to the use of the non-normalized version of the PVI, as opposed to the rate-.