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The relation of emotions and intonation curves
Gavlasová, Radka ; Smékal, Zdeněk (referee) ; Tučková,, Jana (advisor)
This thesis deals with intonation curves and their relation to human emotions. Besides the theoretical part where you can learn about speech production, signal processing and psychological distribution of emotions, there is also a unique database recorded with the help of two professional actors. The main goal of this thesis is to classify created data using artificial neural networks into four classes. Those classes are anger, joy, boredom and sadness. The practical part was implemented in a programming platform called Matlab using Classification Learner app. Features used for this method were variations of fundamental frequency and MFCC. The results were compared with a listening survey so that it could be determined whether the results provided by neural network are relevant to some kind of a human factor. Success rate of the trained models reached 82 %, new data testing reached 75 %. Listening survey confirmed that the results correspond to the assumption of human perception. Better success rate would be accomplished by using a bigger set of higher quality data.
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Voice Analysis for Detection of Diseases
Chytil, Pavel ; Sigmund, Milan (advisor)
Tato disertační práce je zaměřena na analýzu řečového signálu za učelem detekce nemocí ovlivňujících strukturu hlasových orgánů, obzvláště těch, které mění strukturální character hlasivek. Poskytnut je přehled současných technik. Dále jsou popsány zdroje použitých nahrávek pro zdravé a nemocné mlučí. Hlavním učelem této disertační práce je popsat vypočetní postup k odhadu parametrů modelu hlasového zdroje, které umožní následnou detekci a klasifikaci nemocí hlasivek. Poskytujeme detailní popis analýzy řečových signálů, které mohou být odvozeny z parametrických modelů hlasivek.
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The relation of emotions and intonation curves
Gavlasová, Radka ; Smékal, Zdeněk (referee) ; Tučková,, Jana (advisor)
This thesis deals with intonation curves and their relation to human emotions. Besides the theoretical part where you can learn about speech production, signal processing and psychological distribution of emotions, there is also a unique database recorded with the help of two professional actors. The main goal of this thesis is to classify created data using artificial neural networks into four classes. Those classes are anger, joy, boredom and sadness. The practical part was implemented in a programming platform called Matlab using Classification Learner app. Features used for this method were variations of fundamental frequency and MFCC. The results were compared with a listening survey so that it could be determined whether the results provided by neural network are relevant to some kind of a human factor. Success rate of the trained models reached 82 %, new data testing reached 75 %. Listening survey confirmed that the results correspond to the assumption of human perception. Better success rate would be accomplished by using a bigger set of higher quality data.
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Voice and its modulation in human mate choice
Vobecká, Tereza ; Třebický, Vít (advisor) ; Schneiderová, Irena (referee)
1 Abstract Vocal communication is one of the primary means of communication in humans. Information from utterances not providedsolely by speech but also by their acoustic properties (e.g. voice pitch). People tend to associate different acoustic parameters of voice with specific human characteristics, such as physical traits such as body size, sex or personality traits such as dominance or attractiveness. Human voice is dynamic, and it is modulated depending on the inner state of the speaker and external circumstances. For example, the modulation of speaker's voice may be caused by their emotional state or depend on the person they are talking to. This work aims to summarize and review existing literature about the modulation of acoustic parameters of the voice and its effect on perception of others in mate-choice context. Key words acoustics, attractiveness, non-verbal vocalization, fundamental frequency, preferences
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Voice Analysis for Detection of Diseases
Chytil, Pavel ; Sigmund, Milan (advisor)
Tato disertační práce je zaměřena na analýzu řečového signálu za učelem detekce nemocí ovlivňujících strukturu hlasových orgánů, obzvláště těch, které mění strukturální character hlasivek. Poskytnut je přehled současných technik. Dále jsou popsány zdroje použitých nahrávek pro zdravé a nemocné mlučí. Hlavním učelem této disertační práce je popsat vypočetní postup k odhadu parametrů modelu hlasového zdroje, které umožní následnou detekci a klasifikaci nemocí hlasivek. Poskytujeme detailní popis analýzy řečových signálů, které mohou být odvozeny z parametrických modelů hlasivek.
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