This master´s thesis deals with the calculation of parameters that would be able to differentiate healthy speech and speech impaired by hypokinetic dysarthria. There was staged hypokinetic dysarthria, which is a motoric disorder of speech and vocal tract. Were studied speech signal processing methods. Further parameters were studied, which could well differentiate healthy and diseased speech. Subsequently, these parameters were programmed in Python programming language. The next step was to create a web application in Django framework, which is used for the analysis of the dyzartic speech.

Abstract The American president’s serving period always begin with an iconic inaugural address. It is a function wherein the president can unify the audience, ratify the ceremony, and present his political and administrative direction for his term. Promises are a vital rhetorical tool and strategy at the president’s disposal; however, they can also be a demerit if used incorrectly. Within the discipline of pragmatics, promises are included in the category of the commissive speech act: an utterance which binds the speaker to a future course of action. The focus of the present study is what proportion commissive speech acts are used in relation to other speech acts by the four American presidents inaugurated in the 21st century in their inaugural addresses, as well as how these commissive speech acts are realized in terms of various pragmatic features (e.g., vagueness, deictic use, selfpositive representation, and implicature). The methodological approach adopted in thisstudy is both qualitative as well as quantitative in character. To reflect this, the study was operationalized through speech act analysis and political discourse analysis. The findingsshowcase that the presidents affiliated with the Republican party make use of commissive speech acts to a higher degree than their Democratic counterparts. Donald J. Trump appears as a clear outlier with an exuberant amount of commissive speech acts in comparison with the other three presidents. Furthermore, the findings point out that the most common strategy in how commissive speech acts were realised was to shape them as an assertion and using the inclusive deixis “we”. However, Joseph R. Biden diverged from this pattern. Instead, he used explicit promises featuring the individual deixis “I”. In addition, he often employed rhetorical vagueness which made his promises hard to measure if upheld or not.

This work deals with the text-dependent speaker recognition in systems, where just a few training samples exist. For the purpose of this recognition, the voice imprint based on different features (e.g. MFCC, PLP, ACW etc.) is proposed. At the beginning, there is described the way, how the speech signal is produced. Some speech characteristics important for speaker recognition are also mentioned. The next part of work deals with the speech signal analysis. There is mentioned the preprocessing and also the feature extraction methods. The following part describes the process of speaker recognition and mentions the evaluation of the used methods: speaker identification and verification. Last theoretically based part of work deals with the classifiers which are suitable for the text-dependent recognition. The classifiers based on fractional distances, dynamic time warping, dispersion matching and vector quantization are mentioned. This work continues by design and realization of system, which evaluates all described classifiers for voice imprint based on different features.

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