A Computational Model to Predict Changes in Breathiness Resulting From Variations in Aspiration Noise Level

Perception of breathy voice quality is cued by a number of acoustic changes including an increase in aspiration noise level (AH) and spectral slope. Changes in AH in a vowel may be evaluated through measures such as the harmonic-to-noise ratio, cepstral peak prominence (CPP), or via auditory measures such as the partial loudness of harmonic energy and loudness of aspiration noise. Although a number of experiments have reported high correlation between such measures and ratings of perceived breathiness, a formal model to predict breathiness of a vowel has not been proposed. This research describes two computational models to predict changes in breathiness resulting from variations in AH. One model uses auditory measures, whereas the other uses CPP as independent variables to predict breathiness. For both cases, a translated and truncated power function is required to predict breathiness. Some parameters in both of these models were observed to be pitch dependent. The “unified” model based on auditory measures was observed to be more accurate than one based on CPP.