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Recognition of Isolated Words for Electronic Dictionaries
Hrdlička, Pavel ; Szőke, Igor (referee) ; Grézl, František (advisor)
This work is concerned with creation of isolated word recognizer for electronic dictionaires, testing its functionality on data sample and improvement by normalisation and speaker adaptation techniques. Word recognizer is built on HTK (Hidden Markov Model Toolkit). At the beginning of this document, the main aims of the work are set. In the next chapter is theoretical analysis, which describes process of recognition of isolated words with hidden Markov models. Next chapter specifies the speech data, which were used for testing. Other resources for building recognizer, like models, dictionary and grammar are described in next chapter. Before creation of recognizer, it was necessary to solve conversion between the phonemes set which was used in dictionary and set, which uses the recognizer. The recognizer was built with 8~kHz models first, than 16~kHz models were also used. Normalisation and speaker adaptation techniques were used. Obtained data were processed and results are analyzed in separate chapter. Finally is discussed, if the goals of the work were reached and what are the next steps of application development.
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Switching off of Electrical Tools by Voice
Rozsypálek, Lukáš ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
In theoretical part Master’s thesis deals with processing acoustic signal before speech recognition. There are described methods of automatic speech recognition and capture attributes. Those methods are short-term energy of signal, short-term autocorrelation analysis, linear predictive analysis etc. In practical part has been created software, which has to switch off of electrical tool, if the keyword “zastav” has been spoken. In the second part of this thesis software has been optimized for work in real conditions (noise generated by electrical tools).
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Hand Writing Letters Recognition
Jelínek, Radek ; Žák, Jakub (referee) ; Zbořil, František (advisor)
The thesis deals with handwriting recognition and conversion into digital form. Recognition is focused on recognition of letters and finding success when you did not use the dictionary for word recognition. One part of document is compare with commercial applications.
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Convolutional Networks for Historic Text Recognition
Macurová, Nela ; Špaňhel, Jakub (referee) ; Hradiš, Michal (advisor)
This thesis deals with the recognition of historical texts using deep neural networks, specifically the recognition of individual words in Gothic script in Czech. Here is a general overview of convolutional networks and text recognition methods. A dataset was created with real and generated data. The network was trained on generated data and testing on real images of words. This proposed word classification method was not very successful due to different test and training data.
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Convolutional Networks for Historic Text Recognition
Macurová, Nela ; Špaňhel, Jakub (referee) ; Hradiš, Michal (advisor)
This thesis deals with the recognition of historical texts using deep neural networks, specifically the recognition of individual words in Gothic script in Czech. Here is a general overview of convolutional networks and text recognition methods. A dataset was created with real and generated data. The network was trained on generated data and testing on real images of words. This proposed word classification method was not very successful due to different test and training data.
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Pronunciation Validation in Speech Therapy Application
Černý, Patrik ; Peterek, Nino (advisor) ; Vidová Hladká, Barbora (referee)
Title: Pronunciation Validation in Speech Therapy Application Author: Bc. Patrik Černý Institute: Institute of Formal and Applied Linguistics Supervisor: Mgr. Nino Peterek, Ph.D., Institute of Formal and Applied Linguistics Abstract: A goal of this thesis is to design, create and test speech validation method based on current speech recognition algorithms. Resulting software is a speech therapy application for sounds or words training with feedback about pronunciation accuracy. Speech validation is based on CMUSphinx tools and on inaccurate pronunciation generation (using phonetic dictionary). Records with accurate and inaccurate pronunciations has been collected for training and testing purposes. It has been shown, that this design is not appropriate. Thanks to the software design, application can be easily extended by techniques, that could improve validation efficiency. Keywords: speech validation, word recognition, dyslalia, speech therapy appli- cation
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Voice command for a TV set
Černý, Patrik ; Straňák, Pavel (advisor) ; Peterek, Nino (referee)
Title: Voice command for a TV set Author: Patrik Černý Department: Institute of Formal and Applied Linguistics Supervisor: Mgr. Pavel Straňák, Ph.D. Abstract: A goal of this thesis is to create television voice control intended for poeple with speech and movement disorder. This is achieved by interconnecting computer and television. Voice control is based on well-known dynamic time warping algorithm. It has been shown, that due to high and frequent changes in sound intensity the voice control of television is quite a complex task. The word recognition success rate of the final application is not very high, but for the purpose sufficient. Because of application design, program can be easily extended by techniques, that can improve recognition effectivity. Keywords: voice control, word recognition, dynamic time warping, television 1
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Recognition of Isolated Words for Electronic Dictionaries
Hrdlička, Pavel ; Szőke, Igor (referee) ; Grézl, František (advisor)
This work is concerned with creation of isolated word recognizer for electronic dictionaires, testing its functionality on data sample and improvement by normalisation and speaker adaptation techniques. Word recognizer is built on HTK (Hidden Markov Model Toolkit). At the beginning of this document, the main aims of the work are set. In the next chapter is theoretical analysis, which describes process of recognition of isolated words with hidden Markov models. Next chapter specifies the speech data, which were used for testing. Other resources for building recognizer, like models, dictionary and grammar are described in next chapter. Before creation of recognizer, it was necessary to solve conversion between the phonemes set which was used in dictionary and set, which uses the recognizer. The recognizer was built with 8~kHz models first, than 16~kHz models were also used. Normalisation and speaker adaptation techniques were used. Obtained data were processed and results are analyzed in separate chapter. Finally is discussed, if the goals of the work were reached and what are the next steps of application development.
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Hand Writing Letters Recognition
Jelínek, Radek ; Žák, Jakub (referee) ; Zbořil, František (advisor)
The thesis deals with handwriting recognition and conversion into digital form. Recognition is focused on recognition of letters and finding success when you did not use the dictionary for word recognition. One part of document is compare with commercial applications.
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Switching off of Electrical Tools by Voice
Rozsypálek, Lukáš ; Šebesta, Vladimír (referee) ; Sigmund, Milan (advisor)
In theoretical part Master’s thesis deals with processing acoustic signal before speech recognition. There are described methods of automatic speech recognition and capture attributes. Those methods are short-term energy of signal, short-term autocorrelation analysis, linear predictive analysis etc. In practical part has been created software, which has to switch off of electrical tool, if the keyword “zastav” has been spoken. In the second part of this thesis software has been optimized for work in real conditions (noise generated by electrical tools).
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