![]() ![]() Therefore, the thesis starts with theoretical framework on the discipline, including definition, taxonomies and review of state-of-art.įirst, the author looks for acoustic parameters, models and methods that describe voice and speaking style. This interdisciplinary field is located on the borders of computer science, signal processing and linguistic, phonetics, phonology, psychology and sociology and deals also with medical and artistic aspects. The research on paralinguistics has been emerging as a new branch of speech technology for several decades. The crucial aim of research was the automatization of detection of different aspects of speaker profile by machine learning methods. The way we speak was investigated in terms of different functions - starting from paralinguistic aspects like accents or sentence boundaries, ending with non-linguistic information like speaker emotions or attitude. This work combines various aspects of nonlinguistic information conveyed in speech signal - the form and the content of speech that lays beyond linguistic message. Only proper parameterization and statistical analysis methods allow to extract vocal correlates of speaker profile features. Information is mixed in a one-dimensional signal. From the technical point of view, all this Speaker’s states and traits significantly affect the voice itself as well as speaking manner, syntax and semantic content. Voice carries a lot of information: about semantic content we want to communicate, about our identity and also about affective, psycho-social or physical attributes of the speaker. ![]()
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