Automatic Analysis of Phonetic Speech Style Dimensions

We apply automated analysis methods to create a multidimensional characterization of the prosodic characteristics of a large variety of speech datasets, with the goal of developing a general framework for comparing prosodic styles. Our datasets span styles including conversation, fluent reading, extemporized narratives, political speech, and advertisements; we compare several different languages including English, Spanish, and Chinese; and the features we extract are based on the joint distributions of F0 and amplitude values and sequences, speech and silence segment durations, syllable durations, and modulation spectra. Rather than focus on the acoustic correlates of a small number of discrete and mutually exclusive categories, we aim to characterize the space in which diverse speech styles live.