Application of a Landmark-Based Method for Acoustic Analysis of Dysphonic Speech

Aim. Speakers with dysphonia often report difficulty with maintaining intelligibility in noisy envi- ronments; however, there is no objective method for characterizing this difficulty. Landmark -based analysis is a linguistically-motived, knowledge -based speech analysis technique, which may serve as the basis of acoustic tool for describing the intelligibility deficit. As the first step toward development of such a tool, this study examined whether Landmark -based analysis could describe acoustic differences between normal and dysphonic speech. Method. The recordings subjected to the Landmark -based analysis were the first sentence of the Rainbow Pas- sage from 33 speakers with normal voice and 36 speakers with dysphonia. These recordings were selected from the Kay Elemetrics Database of Disordered Voice. The between -group difference was evaluated based on counts of certain Landmarks (LM). Results. The average counts of all LMs were significantly greater in normal speech, t (66.85) = 2.36, P = 0.02. When the group -difference was examined for each LM, dysphonic speech had more [g] and [b] LMs and fewer [s] LMs than normal speech ( P < 0.01 for all cases). A classification tree model identified [+s] and [+b] LMs are the primary predictors for the dysphonic speech. The model ?s misclassification rate was 7.24%. Conclusions. This preliminary investigation demonstrates that LM -based analysis is capable of differentiating dysphonic speech from normal speech. This encouraging result rationalizes future examinations of LM analysis in other areas of interest. For example, LM -based measures could conceivably be used as to quantify general intelligibility, and/or provide insight into underlying mechanisms of intelligibility deficits.