|
|
Gene Detection in DNA Sequences
Roubalík, Zbyněk ; Burgetová, Ivana (referee) ; Martínek, Tomáš (advisor)
Gene detection in DNA sequences is one of the most difficult problems, which have been currently solved in bioinformatics. This thesis deals with gene detection in DNA sequences with methods using Hidden Markov Models. It contains a brief description of the fundamental principles of molecular biology, explains how genetic information is stored in DNA sequences, as well as the theoretical basis of the Hidden Markov Models. Further is described subsequent approach in the design of specific Hidden Markov Models for solving the problem of gene detection in DNA sequences. Is designed and implemented application, which uses previously designed Hidden Markov model for gene detection. This application is tested on the real data, results of these tests are discussed in the end of the thesis, as well as the possible extension and continuation of the project.
|
|
|
Gesture Based Human-Computer Interface
Jaroň, Lukáš ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This masters thesis describes possibilities and principles of gesture-based computer interface. The work describes general approaches for gesture control. It also deals with implementation of the selected detection method of the hands and fingers using depth maps loaded form Kinect sensor. The implementation also deals with gesture recognition using hidden Markov models. For demonstration purposes there is also described implementation of a simple photo viewer that uses developed gesture-based computer interface. The work also focuses on quality testing and accuracy evaluation for selected gesture recognizer.
|
|
|
Handwriting Recognition
Zouhar, David ; Řezníček, Ivo (referee) ; Mlích, Jozef (advisor)
This diploma thesis deals with handwriting recognition in real-time. It describes the ways how the intput data are processed. It is also focused on the classi cation methods, which are used for the recognition. It especially describes hidden Markov models. It also present the evaluation of the success of the recognition based on implemented experiments. The alternative keyboard for MeeGo system was created for this thesis as well. The established system achieved the success above 96%.
|
|
| |
|
|
Speech Recognition Algorithms in FPGA/DSP
Urbiš, Oldřich ; Herout, Adam (referee) ; Szőke, Igor (advisor)
This master's thesis deals with design of speech recognition algorithms with consideration of target technology, which is platform combinating digital signal processing and field programmable gate array. Algorithms for speech recognition includes: feature extraction of Melfrequency cepstral coefficients, hidden Markov models and their evaluation by Viterbi algorithm.
|
|
|
Prediction of p53 Protein Binding Sites
Radakovič, Jozef ; Vogel, Ivan (referee) ; Martínek, Tomáš (advisor)
Protein p53 which is encoded by gene TP53 plays crucial role in cell cycle as a regulator of transcription of genes in cases when cell is under stress. Therefore p53 acts like tumor suppressor. Understanding the pathway of p53 regulation as well as predicting its binding sites on p53 regulated genes is one of the major concerns of modern research in genetics and bioinformatics. In first part of this project we aim to introduce basics from molecular biology to better understand the p53 protein pathway in gene transcription and introduction to analysis of prediction of p53 binding sites. Second part is about implementation and testing of tool which would be able to predict transcription factor binding sites for protein p53.
|
|
|
Prediction of Homolog Protein Sequences
Chlupová, Hana ; Bendl, Jaroslav (referee) ; Martínek, Tomáš (advisor)
Prediction and searching for homologous protein sequences is one of important tasks which are currently being addressed in the area of bioinformatics. According to the determination of homologous sequences of unknown protein sequence it is often possible to determine its structure and function in the organism. For searching homologous sequences, the most frequently used tools are based on direct sequence comparison, profile comparison or on the use of hidden Markov models. There is no universal method better than all others. To satisfy user`s request on needed sequence identity between domains and error rate between founded true positive and false positive pairs, the selection of proper method and its settings is needed. This work is focused to create tool which will help user to choose the best method and its settings according to his requirements. It was created on the basis of the analysis of method results with different settings. In addition, the implemented application offers the possibility to run this method and show its results.
|
|
|
Enhancing the effectiveness of automatic speech recognition
Zelinka, Petr ; Tučková,, Jana (referee) ; Nouza,, Jan (referee) ; Sigmund, Milan (advisor)
This work identifies the causes for unsatisfactory reliability of contemporary systems for automatic speech recognition when deployed in demanding conditions. The impact of the individual sources of performance degradation is documented and a list of known methods for their identification from the recognized signal is given. An overview of the usual methods to suppress the impact of the disruptive influences on the performance of speech recognition is provided. The essential contribution of the work is the formulation of new approaches to constructing acoustical models of noisy speech and nonstationary noise allowing high recognition performance in challenging conditions. The viability of the proposed methods is verified on an isolated-word speech recognizer utilizing several-hour-long recording of the real operating room background acoustical noise recorded at the Uniklinikum Marburg in Germany. This work is the first to identify the impact of changes in speaker’s vocal effort on the reliability of automatic speech recognition in the full vocal effort range (i.e. whispering through shouting). A new concept of a speech recognizer immune to the changes in vocal effort is proposed. For the purposes of research on changes in vocal effort, a new speech database, BUT-VE1, was created.
|
|
|
Isolated word recognition
Vodička, Radek ; Křupka, Aleš (referee) ; Sysel, Petr (advisor)
Main purpose of the thesis is to study the processes and methods of isolated words recognition. In the theoretical part a basic principals are explained. The practical part is about the program creating using these principles in practice. For isolated words recognition Hidden Markov Models (HMM) are used, for obtaining decision symptoms cepstral analysis is chosen.
|
|
|
Signal processing by hidden Markov models
Hampl, Jindřich ; Pfeifer, Václav (referee) ; Sigmund, Milan (advisor)
One of the most common methods for isolated words recognition is based on Hidden Markov models. Speech signal can be considered as a sequence of successive parts of the signal with specific statistical parameters. Hidden Markov model corresponds to the statistical model with the final number of states, which may be useful for signals such as speech. HTK module is a software tools, which is mostly used to work with hidden Markov models.
|
guest ::
