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Speech Recognition For Selected Languages
Schmitt, Jan ; Karafiát, Martin (referee) ; Janda, Miloš (advisor)
This bachelor's thesis deals with recognition of continues speech for three languages - Bulgarian, Croatian and Swedish. There are described basics of speech processing and recognition methods like acoustic modeling using hidden Markov models and gaussian mixture models. Another aim of this work is preparing data for those languages from GlobalPhone database, so they may be used with speech recognition toolkits Kaldi and HTK. With data prepared there are several models trained and tested using Kaldi toolkit.
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Application of Mean Normalized Stochastic Gradient Descent for Speech Recognition
Klusáček, Jan ; Hradiš, Michal (referee) ; Pešán, Jan (advisor)
Umělé neuronové sítě jsou v posledních letech na vzestupu. Jednou z možných optimalizačních technik je mean-normalized stochastic gradient descent, který navrhli Wiesler a spol. [1]. Tato práce dále vysvětluje a zkoumá tuto metodu na problému klasifikace fonémů. Ne všechny závěry Wieslera a spol. byly potvrzeny. Mean-normalized SGD je vhodné použít pouze pokud je síť dostatečně velká, nepříliš hluboká a pracuje-li se sigmoidou jako nelineárním prvkem. V ostatních případech mean-normalized SGD mírně zhoršuje výkon neuronové sítě. Proto nemůže být doporučena jako obecná optimalizační technika. [1] Simon Wiesler, Alexander Richard, Ralf Schluter, and Hermann Ney. Mean-normalized stochastic gradient for large-scale deep learning. In Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, pages 180{184. IEEE, 2014.
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Unsupervised Adaptation of Speech Recognizer
Švec, Ján ; Karafiát, Martin (referee) ; Schwarz, Petr (advisor)
The goal of this thesis is to design and test techniques for unsupervised adaptation of speech recognizers on some audio data without any textual transcripts. A training set is prepared at first, and a baseline speech recognition system is trained. This sistem is used to transcribe some unseen data. We will experiment with an adaptation data selection process based on some speech transcript quality measurement. The system is re-trained on this new set than, and the accuracy is evaluated. Then we experiment with the amount of adaptation data.
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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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Voice Sample database design for speech recognition purposes
Grobelný, Petr ; Malý, Jan (referee) ; Pfeifer, Václav (advisor)
Práce se zabývá rozpoznáváním řeči a tvorbou řečové databáze, která bude sloužit jako trénovací a testovací data pro systém rozpoznávání řeči. Daný korpus je navrhnut jako databáze čtené řeči. V teoretické části je čtenář seznámen s pojmem rozpoznávání řeči a je hlouběji uveden do problematiky. Praktická část se skládá z podrobného postupu vytvoření databáze čtené řeči. Samotná databáze je prezentována na přiloženém médiu. V závěru práce je přiložena potřebná dokumentace celé databáze.
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Speech recognition using Sphinx-4
Kryške, Lukáš ; Uher, Václav (referee) ; Burget, Radim (advisor)
This diploma thesis is aimed to find an effective method for continuous speech recognition. To be more accurate, it uses speech-to-text recognition for a keyword spotting discipline. This solution is able to be applicable for phone calls analysis or for a similar application. Most of the diploma thesis describes and implements speech recognition framework Sphinx-4 which uses Hidden Markov models (HMM) to define a language acoustic models. It is explained how these models can be trained for a new language or for a new language dialect. Finally there is in detail described how to implement the keyword spotting in the Java language.
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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.
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Decoder for key word detection system
Krotký, Jan ; Míča, Ivan (referee) ; Pfeifer, Václav (advisor)
The essay presents the basic characteristics of human speech recognition, describes systems for the detection of key words and further deals with the proposal of each decoder blocks divided into three chapters. The first one describes the operations that are performed before the signal distribution of the framework and the segmentation. The second chapter describes the calculation of short-term energy, the number of zero passes and self-correlative, prediction and Mel-frequency cepstral coefficients. The third chapter, which describes the design of the block decoder, describes the method of dynamic time destruction and the method based on hidden Markov model. The final part of the essay describes decoders working with a speech and a proposal for a simple decoder working with isolated words, which was based issued and tested based on the preceding chapters.
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Voice recognition of standard PILOT-CONTROLLER control commands
Kufa, Tomáš ; Polách, Petr (referee) ; Honzík, Petr (advisor)
The subject of this graduation thesis is an application of speech recognition into ATC commands. The selection of methods and approaches to automatic recognition of ATC commands rises from detailed air traffic studies. By the reason that there is not any definite solution in such extensive field like speech recognition, this diploma work is focused just on speech recognizer based on comparison with templates (DTW). This recognizor is in this thesis realized and compared with freely accessible HTK system from Cambrige University based on statistic methods making use of Hidden Markov models. The usage propriety of both methods is verified by practical testing and results evaluation.
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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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