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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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Modelling Prosodic Dynamics for Speaker Recognition
Jančík, Zdeněk ; Fapšo, Michal (referee) ; Matějka, Pavel (advisor)
Most current automatic speaker recognition system extract speaker-depend features by looking at short-term spectral information. This approach ignores long-term information. I explored approach that use the fundamental frequency and energy trajectories for each speaker. This approach models prosody dynamics on single fonemes or syllables. It is known from literature that prosodic systems do not work as well the acoustic one but it improve the system when fusing. I verified this assumption by fusing my results with state of the art acoustic system from BUT. Data from standard evaluation campaigns organized by National Institute of Standarts and Technology are used for all experiments.
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Automatický expresivní čtený projev
Výkruta, Jan ; Hajič, Jan (advisor) ; Libovický, Jindřich (referee)
Expressive reading is one of possible oral presentations. The text being read is usually prose or poetry. Little has been done in research of what affects expressiveness and whether it can be generated by computers. LibriSpeech, a large scale corpus of read prose and poetry allows us to test generation of expressive reading using machine learning methods. We have focused on poetry as it is generally more expressive. We have prepared methods, that can be used to train more models as well as to prepare different data that could be fed in our learning methods. Moreover, we have developed an extendable application that takes a poem, predicts the reading, visualizes it and plays an audio record generated from the reading using a TTS system. 1
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Modelling Prosodic Dynamics for Speaker Recognition
Jančík, Zdeněk ; Fapšo, Michal (referee) ; Matějka, Pavel (advisor)
Most current automatic speaker recognition system extract speaker-depend features by looking at short-term spectral information. This approach ignores long-term information. I explored approach that use the fundamental frequency and energy trajectories for each speaker. This approach models prosody dynamics on single fonemes or syllables. It is known from literature that prosodic systems do not work as well the acoustic one but it improve the system when fusing. I verified this assumption by fusing my results with state of the art acoustic system from BUT. Data from standard evaluation campaigns organized by National Institute of Standarts and Technology are used for all experiments.
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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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