Classifying place of articulation and palatalization of fricatives based on cepstral coefficients and spectral moments.

Abstract

Hidden Markov models (HMMs) with two types of acoustic features were used to classify fricatives by place of articulation and palatalization status. The data were recordings of 31 native speakers of Romanian who produced a total of 3674 fricatives. Segments from four places (labial, alveolar, postalveolar, and dorsal) were examined, each of which appeared as plain and palatalized (with a palatal secondary articulation). Both the fricatives and the preceding vowels were divided by HMM training into three acoustically uniform regions, corresponding to the three states of the HMM models. Separate sets of monophone HMMs were trained using (a) the first four spectral moments plus rms amplitude and (b) the first five Bark‐cepstral coefficients. Generally, the first and second regions/states of the fricatives were more important in classifying the segments by place, while the third state contributed more to the classification by palatalization status. The success of the classification depended on the specific combination of predictor variables (acoustic features and regions) used. Thus, the overall accuracy in classifying segments according to place or palatalization ranged from 62% to 95%. These analyses shed light on the differential distribution over time of acoustic features related to place and palatalization.