A Simple Fingerprint Approach to Extracting the Global Prosodic Properties from Field Data
The paper reports a method to create a speaker’s prosodic fingerprint based on the global characteristics of the pitch movement. Prosodic fingerprint is the distribution of f0 in the low, middle, and high ranges and the distribution of pitch movements from one range into other [Šimko et al. 2017]. This fully automated method can be used to classify the records and to provide the reference level for more sophisticated analysis of the pitch movement and intonation strategies. We evaluate the method by applying it to the spontaneous Russian spoken data recorded in different regions. We model the correlation between the fingerprint and sociolinguistic features such as age, gender, and region. The results of this analysis allow to formulate several sociolinguistic hypotheses that can further be tested with a more detailed analytic technique.