National Repository of Grey Literature 24 records found  1 - 10nextend  jump to record: Search took 0.03 seconds. 
State of the art speech features used during the Parkinson disease diagnosis
Bílý, Ondřej ; Smékal, Zdeněk (referee) ; Mekyska, Jiří (advisor)
This work deals with the diagnosis of Parkinson's disease by analyzing the speech signal. At the beginning of this work there is described speech signal production. The following is a description of the speech signal analysis, its preparation and subsequent feature extraction. Next there is described Parkinson's disease and change of the speech signal by this disability. The following describes the symptoms, which are used for the diagnosis of Parkinson's disease (FCR, VSA, VOT, etc.). Another part of the work deals with the selection and reduction symptoms using the learning algorithms (SVM, ANN, k-NN) and their subsequent evaluation. In the last part of the thesis is described a program to count symptoms. Further is described selection and the end evaluated all the result.
Emotional State Recognition Based on Speech Signal Analysis
Čermák, Jan ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The thesis is focused on the emotional states classification in the Matlab program, using neural networks and the classifier which is based on a combination of Gaussian density functions. It deals with the speech signal processing; the prosodic and spectral signs and the MFCC coefficients were extracted from the signal. The work also deals with the quality evaluation of individual signs of which the most suitable were chosen in order to provide the correct classification of emotional states. In order to identify the emotional states, two different methods were used. The first method of classification was the use of neural networks with differently selected parameters, and the second method was the use of the Gaussian mixture model (GMM). In both methods, a database of emotional utterances was divided into the training group and the test group. The testing was based on a method independent of the speaker. The work also includes the comparison of individual analyzed methods as well as the representation and comparison of the results. The conclusion comprises a proposition for the best parameters and the best classifier for the recognition of the speaker’s emotional state.
Linear prediciton and cepstral synthesis of speech signal in the TTS system
Mekyska, Jiří ; Stejskal, Vojtěch (referee) ; Smékal, Zdeněk (advisor)
This work deals with a linear prediction and cepstral synthesis of speech signal in the TTS (Text-to-Speech) systems with the opportunity of modeling the prosody. The work contains a description of speech signal in acoustic and phonetic plane, the principle of speech production and the way we can figure the speech signal in time and frequency domain. Next, there is the TTS block structure mentioned, whereas each block has its own detailed description. In the work, the modeling of prosody using the three most important suprasegmental features (fundamental tone, continuation and speech intensity) is also described. At the end of this work, there is a design and realization of universal Czech TTS system which is based on the speech synthesis in frequency domain. This system is implemented in program MATLAB.
Database of vocal samples of human emotions
Hlavica, Michal ; Přinosil, Jiří (referee) ; Atassi, Hicham (advisor)
In this bachelor work is analyzed theory of emotions, how emotions arise and how they are physiologically expressed by human body. How these physiological expressions and emotions reflect into the human speech. Then is described process of creating of speech and basic prosodic and acoustic parameters relevant for research. Theory of creating of databases is described here as well, which is quality ground for database itself. The database is also part of this thesis and they are records cut from television programmes and serials. The next very important issue is description of software tool for subjective evaluating of databases, which was created as a part of this thesis. It was created in C++ language with help by compiler Builder C++ . Also a short analysis of exemplary records for every emotion is done here. This analysis deals with basic frequency, intensity and first three formants.
Application for the calculation of speech features describing hypokinetic dysarthria
Hynšt, Miroslav ; Mekyska, Jiří (referee) ; Kiska, Tomáš (advisor)
This thesis is about design and implementation of application for computing speech parameters on people with Parkinson disease. At the beginning is generaly described Parkinson disease and Hypokinetic dysarthria and how it affects the speech and speech parameters when it occurs. Mainly there are described areas of speech like phonation, prosody, articulation and fluent speech. As a part of next topic this thesis describes specific speech parameters with bigger meaning during diagnosis Parkinson disease and it's progress over the time. There are also mentioned few significant studies dealing with examination of speech of the subjects with diagnoses of Parkinson disease and computing some speech parameters in order to analyze their speech impairments. Part of the thesis is description of implemented standalone application for calculating, exporting and visualizing of speech parameters from selected sound records.
Automatic / Automated recogniton of emotional states based on utterance analysis
Pfeifer, Leon ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis deals with the analysis of human emotional states. The thesis consists of three parts. The first part is charcterize, the process of speech generating, from phonetic and psychological poin of view. In the second part there are proccesed metods and contextual things.(preprocessing of signal, voice activity detector). For calculation fundamental Frequency it was used metod of central clipping, another used metod is formant frequency analyse and the last is metod of determinatin of nuber of thorns and planes. In the thirt part there are proccesesed results of measurements performed by particural metods. It was scorred five different emotional states: neutral, anger, happiness, sadness and surprise. At the end of this part there are discussed results for each metod.
Identification of emotional state using speech signal analysis
Navrátil, Michal ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The diploma thesis deals with the analysis of human emotional states speaker by the help of analyse speech signals. The thesis has two parts. In the first part, the process of speech generating is described in addition to the description of the commonly used pre-processing methods such as denoising or preemphasis. The first part also deals with the major and minor prosody features, these features are: the fundamental frequency, energy, spectral features and time domain features such as the speech rate. The second part of this thesis deals with a task of emotion recognition from the speech signal. When we accumulate sufficient of the number of recordings emotive state will be able to rekognize emotive state with high probability. All project is prepared for use in real time. The last part of this thesis thesis contains description and results of the experiments made on a large number of speech records.
Voice Conversion
Schwarz, Ivan ; Szőke, Igor (referee) ; Černocký, Jan (advisor)
Thesis is dedicated to the making of a system for voice conversion. To methods, which alter voice of one person in a way, that it could be possible for listener to mislead it for someone elses voice. In the first part, Harmonic plus Noise Model (HNM) is described. Signal analysis and synthesis are its main purposes. Methods of voice conversion are considered in the second part. Prosodic modifications are introduced at first and then modification of a spectral envelope is discussed (Especially aplication of conversion matrices). Dynamic Time Warping (DTW) and Linear Prediction Coding (LPC) methods are explained briefly. In last section, implementation process is described and achived results are discussed. Ways of further development are suggested in summary.
Teaching Suprasegmental Pronunciation Features in English through Authentic Documents
NOVÁKOVÁ, Adéla
The aim of the bachelor thesis is to enrich the existing ways of teaching suprasegmental pronunciation features in English pronunciation in secondary schools with a focus on the possibilities of using authentic materials. In the introductory section, we will introduce the nature of the suprasegmental pronunciation features, which we investigate in this thesis. Then, we will summarize basic didactic principles of teaching second language pronunciation, focusing primarily on the pronunciation of suprasegmental pronunciation features. Next, we will map the existing ways of presenting and practising suprasegmental phenomena, based on the analysis of exercises in selected English language textbooks for secondary schools aimed at practising suprasegmental phenomena. We will define terminologically the notion of authentic material and specify the types of authentic materials that can be used to teach second language pronunciation. Subsequently, we will propose a set of activities based on selected authentic materials to enrich existing types of exercises aimed at pronunciation training.
Sub-types of hypokinetic dysarthria in patients with moderete Parkinson's disease
Adamják, Adam ; Kováč, Daniel (referee) ; Mekyska, Jiří (advisor)
This final thesis deals with the research of Parkinson's disease, hypokinetic dysarthria, and acoustic and statistical analyses. Hypokinetic dysarthria is a speech disorder that is a typical manifestation of Parkinson's disease, a neurodegenerative disease that affects approximately 2% of the population over the age of 65. The aim of this work is to reveal the subtypes of hypokinetic dysarthria, based on clinical parameters, acoustic analysis, and statistical analysis. In the acoustic analysis, parameters that examine the area of phonation, prosody, articulation, and speech tempo have been implemented. Subsequently, a statistical analysis was processed, thanks to which it was possible to reveal the subtypes of hypokinetic dysarthria.

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