National Repository of Grey Literature 19 records found  1 - 10next  jump to record: Search took 0.00 seconds. 
Identification Of Parkinson’S Disease Using Acousticanalysis Of Poem Recitation
Mucha, Ján
Parkinson’s disease (PD) is the second most frequent neurodegenerative disorder. It is estimated that 60–90% of PD patients suffer from speech disorder called hypokinetic dysarthria (HD). The goal of this work is to reveal influence of poem recitation on acoustic analysis of speech and propose concept of Parkinson’s disease identification based on this analysis. Classification methods used in this work are Random Forests and Support Vector Machine. The best achieved accuracy of disease identification is 70.66% with 59.25% sensitivity for Random Forests classifier fed mainly with articulation features. These results demonstrate a high potential of research in this area.
Analysing Tool for Generating of Drum Triggers from Downmix Record
Konzal, Jan ; Mucha, Ján (referee) ; Přikryl, Lubor (advisor)
This thesis deals with the design and implementation of a tool for generating drums triggers from a downmix record. The work describes the preprocessing of the input audio signal and methods for the classification of strokes. The drum classification is based on the similarity of the signals in the frequency domain. Principal component analysis (PCA) was used to reduce the number of dimensions and to find the characteristic properties of the input data. The method support vector machine (SVM) was used to classify the data into individual classes representing parts of the drum kit. The software was programmed in Matlab. The classification model was trained on a set of 728 drum samples for seven categories (kick, snare, hi-hat, crash, ride, kick + hi-hat, snare + hi-hat). The success of the system in the classification is 75 %.
Musical instruments recognition from audio records using Music information retrieval techniques
Kárník, Radoslav ; Mucha, Ján (referee) ; Kiska, Tomáš (advisor)
This paper discusses design and implementation of classifying system for recognition of musical instruments from audio records with use of Musical Information Retrieval techniques. In the first part, paper describes parameters used for instrument classification, calculation of said parameters from records and reduction of feature vector. Next part is devoted to tuning and implementation of various classifiers with focus on neural networks. These classifiers ar further tested on records from IRMAS dataset wchich contain 11 musical instruments playing solo or with other instruments. Results of classifiers tested on different parameters and different numbers of instruments are discussed in the last part.
Music mood and emotion recognition using Music information retrieval techniques
Smělý, Pavel ; Mucha, Ján (referee) ; Kiska, Tomáš (advisor)
This work focuses on scientific area called Music Information Retrieval, more precisely it’s subdivision focusing on the recognition of emotions in music called Music Emotion Recognition. The beginning of the work deals with general overview and definition of MER, categorization of individual methods and offers a comprehensive view of this discipline. The thesis also concentrates on the selection and description of suitable parameters for the recognition of emotions, using tools openSMILE and MIRtoolbox. A freely available DEAM database was used to obtain the set of music recordings and their subjective emotional annotations. The practical part deals with the design of a static dimensional regression evaluation system for numerical prediction of musical emotions in music recordings, more precisely their position in the AV emotional space. The thesis publishes and comments on the results obtained by individual analysis of the significance of individual parameters and for the overall analysis of the prediction of the proposed model.
Patient assessment system based on mHealth techniques
Kulinich, Viacheslav ; Mucha, Ján (referee) ; Mekyska, Jiří (advisor)
This bachelor thesis is focused on the possibility of examining patients using an electronic questionnaire based on mHealth techniques. In the first two chapters of this work is included the issue of patient examination, the function that must fulfill the electronic questionnaire, the research of existing types of mobile applications and the description of the selected type. The following chapters contain the process of creating web applications, implementation of client and server part, their communication, used security elements and brief description of graphical interface. The result is a functional progressive web application that has been tested successfully and is published on the Internet.
New Methodology Of Parkinsonic Dysgraphia Analysis By Online Handwriting Using Fractional Derivatives
Mucha, Ján
Parkinson’s disease (PD) is the second most frequent neurodegenerative disorder. One typical hallmark of PD is disruption in execution of practised skills such as handwriting. This paper introduces a new methodology of kinematic features calculation based on fractional derivatives applied on PD handwriting. Discrimination power of basic kinematic features (velocity, acceleration, jerk) was evaluated by classification analysis (using support vector machines and random forests). For this purpose, 37 PD patients and 38 healthy controls were enrolled. In comparison to results reported in other works, we proved that FDE in online handwriting analysis brings promising improvements. The best result of multivariate analysis was achieved with 83:89% classification accuracy in combination with 5 features using only one handwriting task (overlapped circles). This study reveals an impact of fractional derivatives based features in analysis of Parkinsonic dysgraphia.
Application for dysarthria examination using test 3F for Android
Sarker, Joy Tomáš ; Mekyska, Jiří (referee) ; Mucha, Ján (advisor)
This bachelor thesis focuses on diagnosing dysarthria thru a diagnosis apparatus called “Test 3F dysarthria profile“. During an examination with the apparatus the examined person undergoes 45 exercises that are meant to test respiration, phonation, phonetics, and the volubility of certain speech organs. The examiner, a clinical speech therapist, assesses the execution quality of each exercise with a number from 0 to 2. On the grounds of received points from all the exercises the level of dysarthria is diagnosed. The 3F test in this bachelor thesis is implemented as an Android application for Android devices and is supplemented by a partial automation of the examination based on an acoustic analysis of recorded speech of the examinee. The recorded speech is pre-processed by segmentation into 25 ms long frames using Hamming window. From this aforementioned speech recording we can determine speech fundamental frequency, jitter, and shimmer. The main goal and outcome is the creation of a modern mobile application for Android devices which, with the help of the 3F test, will make diagnosing dysarthria easier.
Library for Python used for dysarthric speech parameterization
Koutný, Tomáš ; Galáž, Zoltán (referee) ; Mucha, Ján (advisor)
Bachelor thesis is focused on parameterization of dysartoric speech. Attention is paid to methods of Speech Signal Analysis for Parkinson's disease, modern parametrization techniques, which are designed to quantify the damage of motoric aspects of speech and implementation of selected parameters in Python. The main goal of this work was to create a parameter library that is realized in the PyCharm development environment.
Recognizing the historical period of interpretation based on the music signal parameterization
Král, Vítězslav ; Mucha, Ján (referee) ; Kiska, Tomáš (advisor)
The aim of this semestral work is to summarize the existing knowledge from the area of comparison of musical recordings and to implement an evaluation system for determining the period of creation using the music signal parameterization. In the first part of this work are describe representations which can music take. Next, there is a cross-section of parameters that can be extracted from music recordings provides information on the dynamics, tempo, color, or time development of the music’s recording. In the second part is described evaluation system and its individual sub-blocks. The input data for this evaluation system is a database of 56 sound recordings of the first movement of Beethoven’s 5th Symphony. The last chapter is dedicated to a summary of the achieved results.
Acoustic call analysis application for Android system
Hejda, Jakub ; Mucha, Ján (referee) ; Mekyska, Jiří (advisor)
The telemedicine’s capabilities are rapidly expanding due to technological advances in a smarphone development. The goal of this thesis was to suggest the architecture and prepare the design providing acquisition, processing and synchronization of voice para- meters recorded by patients with Parkinson’s disease and to implement such system. The architecture was completed successfully, it consists of the mobile application able to record patient’s calls, the server application introducing an interface to store and synchronize the data and to provide them to the web application, where doctors can see the data and analyze it. Implementation of the server application was finished according to the design and to the requirements for robustness and security as well as the web application. By an extension of the existing mobile application for recording voice calls there was developed a huge system for the analysis of this disease.

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1 Mucha, Jakub
5 Mucha, Jan
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