|
| |
|
|
Identification of persons via voice imprint
Mekyska, Jiří ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
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.
|
|
|
Automatic speech recordings segmentation tool
Santa, Roman ; Zvončák, Vojtěch (referee) ; Kováč, Daniel (advisor)
Nástroj pre automatickú segmentáciu spracováva nahrávky reči a extrahuje hovorené slovo z nahrávok. Je dôležité, aby pokročilá analýza pracovala iba s rečovými časťami z nahrávky. Nástroj na segmentáciu má ulahčiť spracovanie nahrávok pre analýzu rozdielov medzi hláskami pacientov s parkinsonovou chorobou a tými zdravými. Cieľ tejto práce je navrhnúť a otestovať detektory reči s Google WebRTC detektorom a vybrať ten najvhodnejší detektor reči s minimálnym počtom chýb. Ďalej, vytvoriť nástroj na segmentáciu nahrávok a otestovať rozpoznávanie reči pomocou dynamic time warping. Bola použitá databáza poskytnutá laboratóriom pre analýzu mozgových ochorení. Obsahuje české a maďarské nahrávky s rovnakým počtom mužských a ženských pacientov a aj rovnakým počtom zdravých pacientov a pacientov s parkinsonovou chorobou. Najlepšie výsledky v testoch dosiahol detektor na základe energie reči. Nebol zistený žiaden rozdiel v presnosti detektoru pri spracovaní mužských a ženských nahrávok alebo nahrávok zdravých či chorých pacientov. Nahrávky s nízkym odstupom signálu od šumu boli náročnejšie na spracovanie s frekvenciou chýb od 12%. Na základe výsledkov, bol navrhnutý nový detektor pre spracovanie úplnej nahrávky. Na záver bol testovaný algoritmus pre rozpoznávanie podobnosti reči na základe melovských kepstrálnych koeficientov.
|
|
|
Recognition methods for biosignals
Juračka, Zdeněk ; Vítek, Martin (referee) ; Kolářová, Jana (advisor)
The thesis is focused on the recognition methods study used in one-dimensional signal processing. A lot of recognition methods exist, this thesis briefly describes the principle of some of them, e.g. artificial neural networks, fuzzy systems, expert systems and decision trees. Dynamic time warping (DTW) method has been chosen for signal processing available from UBMI database. DTW can be used as a non-linear signal processing method. The result of this method is to determine the similarity of two compared signals on the basis of their distance calculation. One of the reasons for choosing this method was the possibility of various length signal processing. The principle of the method as well as the calculation of the distance between two input data sequences is described in the thesis. DTW path finding method is also mentioned. The method was applied on randomly selected numbers and a set of simulated signals. The method was applied to ECG and action potential signals recorded on the isolated rabbit heart. DTW was used to evaluate shape changes of these signals in repeated phases of the experiment known as ischemia and reperfusion. Selected cardiac cycles were detected and included into different experiment phases on the basis of calculated distance results using DTW. Sensitivity was selected as an evaluative criterion of this classification method. It reached a value of 65%. DTW algorithm was further tested on the selected cardiac cycle mapping to the corresponding minute record in the selected experiment phase. It reached a sensitivity of 68.3%. The motion artifact appearance was monitored using DTW on AP signals. The method functioned more precisely on signals measured in ischemia phases. Along with the above mentioned, the thesis discusses all aspects of heart electrical manifestation activities called as ECG signals and action potentials, such as origin, propagation, recording, post-processing and measuring out.
|
|
|
A tool for simultaneous playback of multiple composition interpretations
Švejcar, Michael ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
The purpose of this Bachelor’s thesis was to create a piece of software which enables the user to simultaneously play back multiple interpretations of a musical piece and switch between them instantaneously. This was achieved using the App Designer in the MATLAB environment, which is intended for developing applications with graphical user interface. The key to the development of the application was especially the use of available toolboxes and algorithms for computing chromagrams and multiscale dynamic time warping. The final IntSwitcher player enables the user to load two recordings of interpretations of one song. Chromagrams which characterize the individual recordings in terms of tonal development over time are first calculated from the input files. After that, the multiscale dynamic time warping method is applied on the chromagrams, which outputs the warping path. The warping path in this case is a matrix, in which musically corresponding samples of loaded audio files are assigned together with the resolution of 50 ms. From this, the corresponding time position of currently inactive track is computed along with its slider position. If the user switches the currently played recording, the second track starts playing in the same part of composition, even if that part is at a different time in each of the individual recordings. The final software is an appropriate tool for studying differences between various interpretations of the same musical piece.
|
|
|
Online detection of simple voice commands in audiosignal
Zezula, Miroslav ; Březina, Lukáš (referee) ; Krejsa, Jiří (advisor)
This thesis describes the development of voice module, that can recognize simple speech commands by comparation of input sound with recorded templates. The first part of thesis contains a description of used algorithm and a verification of its functionality. The algorithm is based on Mel-frequency cepstral coefficients and dynamic time warping. Thereafter the hardware of voice module is designed, containing signal controller 56F805 from Freescale. The signal from microphone is conditioned by operational amplifiers and digital filter. The third part deals with the development of software for the controller and describes the fixed point implementation of the algorithm, respecting limited capabilities of the controller. Final test proves the usability of voice module in low-noise environment.
|
|
|
Dynamic Time Warping in Biosignal Processing
Kubát, Milan ; Kozumplík, Jiří (referee) ; Klimek, Martin (advisor)
This work is dedicated to dynamic time warping in biosignal processing, especially it´s application for ECG signals. On the beginning the theoretical notes about cardiography are summarized. Then, the DTW analysis follows along with conditions and demands assessments for it’s successful application. Next, several variants and application possibilities are described. The practical part covers the design of this method, the outputs comprehension, settings optimization and realization of methods related with DTW
|
|
|
Classification of cardiac cycles
Lorenc, Patrik ; Škutková, Helena (referee) ; Vítek, Martin (advisor)
This work deals with the classification of cardiac cycles, which uses a method of dynamic time warping and cluster analysis. Method of dynamic time warping is among the elderly, but for its simplicity compared to others is still very much used, and also achieved good results in practice. Cluster analysis is used in many fields such as marketing or just for biological signals. The aim of this work is a general introduction to the ECG signal and the method and implementation of dynamic time warping algorithm. Subsequently, cluster analysis and finally the creation of the user interface for the algorithms.
|
|
|
Dynamic time warping in biosignal processing
Novobilský, Petr ; Provazník, Ivo (referee) ; Kolářová, Jana (advisor)
The thesis deals with one of the non-linear methods for signal processing - dynamic time warping (DTW). The method observes shape changes, which should be used in biomedical signals processing. The thesis involves the method description and consecution for finding DTW optimal way. The method is applied on the number series in the edutainment program, on the group of simulated signals and real electrocardiograms (ECG). ECG recordings were gained by performing experiments on the Masaryk University and their aim was clarifying the influence of voltage-sensitive dye on the heart tissue. One-lead ECG was described in time domain, frequency domain, time-frequency domain and subsequently remitted to DTW algorithm. The method outcomes evaluates the diversity rate of ECG signals obtained in each experiment stages. During the data evaluation were followed up the changes in process of the tension-sensible paint application and the stage of scouring toward control. The difference of elaborating signals group was verified in the time domain (37,5 %), in the frequency domain (75 %) and in the time-frequency domain (25 %). However, due to the small data group was not possible to explicitly approve the activity of voltage-sensitive dye on the heart tissue and to determinate limiting value of minimum algorithm way DTW for each heart round electrocardiogram classification. In the more data group analysis it is supposed to manifest the trend of growth heart round ECG differences in the stage of staining toward the stage of scouring.
|
|
|
Searching Acoustic Patterns in Speech Data without Recognition
Skácel, Miroslav ; Fapšo, Michal (referee) ; Černocký, Jan (advisor)
This work investigates into methods for words, word phrases and longer segments detection in large speech data sets in an unsupervised way. At first, basics for the given topic and principles of modern methods for searching of repeating objects are introduced. The representation and segmentation of the input data are described. Techniques for object detection in speech are presented. The description of found motifs modelling follows. The next step defi nes data sets for experiments in which spoken term detection by an example is performed. The system requirements are described. In the conclusion, the work is summarised and suggestions for further development are discussed.
|
guest ::
