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Very limited Vocabulary Speech Recognizer
Vystavěl, Kamil ; Míča, Ivan (referee) ; Sysel, Petr (advisor)
This bachelor thesis deals with the implementation of voice diagnostic method with limited number of recognized words in Matlab environment. Recognizer is designed for recognition of isolated words and is based on the dynamic programming method. This method is realized by the dynamic time warping algorithm (DTW). Features of the speech signal are calculated by methods of short-term analysis in time and frequency domain and by methods that are based on cepstral analysis and linear predictive analysis. The representation of the word, which is generated from its features, is suitable for quantifying the degree of similarity with the representation of another word. In order to achieve the highest degree of similarity, the dynamic time warping algorithm eliminates influence of fluctuation of the speech rate by non-linear normalization time axis of one of the compared words. The degree of the similarity of the two compared words is enumerated as the words’ distance. The representations of known words are stored in a word-book. The unknown word is compared with all words in the word-book and recognizer calculates distances between every known word and the unknown word. The unknown word is defined as identical with the known word that has the shortest distance to the unknown word. The successfulness depends mainly on the choice of the features.
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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.
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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
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Dynamic time warping in biological signal processing
Brus, Lukáš ; Švrček, Martin (referee) ; Kolářová, Jana (advisor)
The Method of dynamic time warping is one of the modern scientific methods. It can be used for optimalization of analysis and classification of diagrams with biological signals. One part of the bachelor's thesis is to witness the generation of a biological process while studying the electrocardiogram and ECG classifications. The final part of the thesis is the discussion of the dynamic time warping and using these methods on a real data base of ECG signals from an experiment on an animal heart. This thesis mentions the function of DTW and also discusses a self-designed program for ECG diagnosing. This program, entitled ECG diagnose, is used for characterizing changes of the ECG signals during experiments performed on animal hearts.
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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.
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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.
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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.
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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.
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Voice commands recognition in audiosignal
Šrámek, Martin ; Grepl, Robert (referee) ; Krejsa, Jiří (advisor)
You are holding in your hands the Bachelor thesis which deals with design and realizing of isolated voice recognition system. The motivation of this thesis was an interest in remote control of robotic mechanisms by voice and a research of speech signal processing. It is widely developed these days. The thesis is divided into two parts. The first one is concerned with summarizing of recognition knowledge, in the second one this knowledge is used in design of a system.
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Dynamic Time Warping for Vehicle Classification
Halachkin, A.
This work focuses on the dynamic time warping for vehicle classification. The theoretical part includes the dynamic time warping algorithm description. The DTW module in Python, that was created during this work, is subsequently applied for the recognition of vehicle types by their side profiles based on the DTW.
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