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.

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.

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.

Title of the thesis: Developing pronunciation through musical activities in French lessons Keywords: communicative approach, phonetics, phonology, pronunciation, prosody, activity, music, rhythm, rhythmisation, melody, tempo, intonation, accent, song, rap, facial expressions Abstract: This thesis deals with the teaching of French phonetics, considers the status of phonetics in communicatively oriented teaching, and comes to the fact that the teaching of phonetics and phonology is not a priority in the communicative approach. The work demonstrates the importance of such teaching, and therefore explores how the teaching of pronunciation or some of its components could be made more attractive. Based on the proven relationship of music and language, both as auditory phenomena, this thesis approaches the interwoven elements of these two areas. The aim is to explore how the musical elements, such as: rhythm, melody, tempo, phrasing, etc., could be used in the teaching of French pronunciation - especially at the suprasegmental level. The work offers a basic inventory of exercises which benefit from this characteristic and which has been verified in practice, and in the final analysis summarises their effectiveness in foreign language teaching.

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.

While the linguistic concept of politeness has been thoroughly analyzed, the same does not apply to its interpreting. The present theoretical-empirical work describes the means for expressing politeness grouped by G. Leechʼs maxims of politeness. The empirical part analyzes recordings of simultaneous interpretation from media and European Parliament settings. This is a quantitative study and the outcome is the number of means for expressing politeness which the interpreters conveyed into Czech. On average and in all of the material 65,7 % of means for expressing politeness were conveyed into Czech in compliance with the maxims. The means analyzed are prosody, non-verbal communication, modality, personal reference, etc. An equivalent interpretation of means of politeness was deemed desirable. The thesis verifies the hypothesis whether the level of politeness significantly increased in comparison with the original speeches. Key words: politeness, pragmatics, illocutionary act, maxims of politeness, face, modality, prosody, non- verbal communication, Czech, English, interpreting, equivalence, US presidential debate, Obama, Romney, Common Agricultural Policy, European Parliament, Catherine Ashton, forms of address

A Dissertation Abstract to Phonology of Masoretic Hebrew II Accents As Prosody Jiří Hedánek řjh (2017) PMH II - Abstract Charles University, Faculty of Arts, Prague 1 Abstract The dissertation Phonology of Masoretic Hebrew: Accents as Prosody (2017) interprets Tiberian 'accents' as speech prosody marking. Traditionally, they are explained as signs for accenting, singing or syntax. But only some were placed on accents. They do not map well to music which has been shaped by local traditions more than the mark-up. Syntactic interpretation is based on dividing marks but many diverse marks link, no links lead outside of verses, some words have two different marks and simple verses often miss stronger dividers. Interpreting them as prosody explains why they gravitated to accent positions; why different musical renditions developed; why they often agree with syntax and sometimes they do not. First a general concept of prosody units is put forward. This is applied to Masoretic Hebrew and the focus turns to intonation. The previous dissertation Phonology of Masoretic Hebrew (2011) analyzed siluq, atnach, segolta, zaqeph, revia (also mugrash, and establishing garsha as a unit), geresh, gershayim, tevir, mercha (also kphula), tiphcha, tarcha and dechi. The 2017 dissertation analyzed (from printed editions, manuscripts...

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.