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Emotional State Recognition and Classification Based on Speech Signal Analysis
Černý, Lukáš ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis focuses on classification of emotions. Thesis deals about parameterization of sounds files by suprasegment and segment methods with regard for next used of these methods. Berlin database is used. This database includes many of sounds records with emotions. Parameterization creates files, which are divided to two parts. First part is used for training and second part is used for testing. Point of interest is self-organization network. Thesis includes Matlab´s program which can be used for parameterization of any database. Data are classified by self-organization network after parameterization. Results of hits rates are presented at the end of this diploma thesis.
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Speech Enhancement using Cancelling of Dissonant Components
Studený, Radim ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This work is supposed to remove interferences from speech signal and so increase its clarity, quality of degraded signal and signal-to-noise ratio. The most common sources of interference could be street noise, wind coming on a microfon, speech on the background or music.The metod described in this work remove frequence bands of a signal, which in relation to the fundamental frequency of a speech are disonant. Be specific, to reference tone C there are F#, B a C# tones.
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SW support for emotional state analysis
Lněnička, Jakub ; Míča, Ivan (referee) ; Smékal, Zdeněk (advisor)
The goal of my bachelor work is the description of SW tool with the graphic interface which can be made use of for the purpose of developing the multimodal emotional databases. In its beginning my work deals with the description of the parts of the human body that produce voice (vocal cords) and their functioning. The text is a description of the procedure of transferring the human voice into the digital form where a special attention is paid to the parameters of the speech signal with the emphasis on the description of the symptoms that serve to the purpose of defining the chosen emotions. This work deals with the categorization of emotions and the description of some of them. In the closing part the K-NN classificator is described that serves to the recognition of the individual feelings by means of a produced software.
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Speech Enhancement using Cancelling of Dissonant Components
Studený, Radim ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This work is supposed to remove interferences from speech signal and so increase its clarity, quality of degraded signal and signal-to-noise ratio. The most common sources of interference could be street noise, wind coming on a microfon, speech on the background or music.The metod described in this work remove frequence bands of a signal, which in relation to the fundamental frequency of a speech are disonant. Be specific, to reference tone C there are F#, B a C# tones.
|
|
|
SW support for emotional state analysis
Lněnička, Jakub ; Míča, Ivan (referee) ; Smékal, Zdeněk (advisor)
The goal of my bachelor work is the description of SW tool with the graphic interface which can be made use of for the purpose of developing the multimodal emotional databases. In its beginning my work deals with the description of the parts of the human body that produce voice (vocal cords) and their functioning. The text is a description of the procedure of transferring the human voice into the digital form where a special attention is paid to the parameters of the speech signal with the emphasis on the description of the symptoms that serve to the purpose of defining the chosen emotions. This work deals with the categorization of emotions and the description of some of them. In the closing part the K-NN classificator is described that serves to the recognition of the individual feelings by means of a produced software.
|
|
|
Emotional State Recognition and Classification Based on Speech Signal Analysis
Černý, Lukáš ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis focuses on classification of emotions. Thesis deals about parameterization of sounds files by suprasegment and segment methods with regard for next used of these methods. Berlin database is used. This database includes many of sounds records with emotions. Parameterization creates files, which are divided to two parts. First part is used for training and second part is used for testing. Point of interest is self-organization network. Thesis includes Matlab´s program which can be used for parameterization of any database. Data are classified by self-organization network after parameterization. Results of hits rates are presented at the end of this diploma thesis.
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