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Czech-Slovak Statistical Machine Translation
Astaloš, Lukáš ; Kouřil, Jan (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to design, implement and evaluate the translation system capable of translating texts from Czech to Slovak language. It describes theoretical foundations of statistical machine translation and then the phase of design and development of system. The chosen strategy was to build phrase-based translation model using one large parallel corpus in combination with language model from local institute of linguistics. The statistical machine translation Moses was used to achieve this goal. The vocabulary translation of unknown words using stemming was proposed and tested. Precision of build system was evaluated with BLEU score and it achieved comparable results with other systems.
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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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Fast and Accurate Keyword Spotting System
Lenčéš, Marián ; Karafiát, Martin (referee) ; Schwarz, Petr (advisor)
This bachelor's thesis deals with fast and accurate detection of keywords from audio records. The aim of was to study possibilities of word detection and to create several types of language models. These were then to be compared to each other. We focus here on the detection of keywords from English spoken audio records.
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Intelligent Shopping List
Doubek, Milan ; Herout, Adam (referee) ; Szőke, Igor (advisor)
This thesis deals with creating of unique shopping lists management application and we used the newest startup techniques and principles during its development. All our hypotheses were tested by early adopters and the new courses of development were based on their feedback. The result of this thesis is a mobile application for Android operating system which is placed on Google Play market and two its components which will extend the application on the market. The main component is inteligent sorting of items on the shopping list by the supermarket model, which is created from last purchases in this supermarket. The second one is web application enabling us send new shopping lists to the mobile device.
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Finite State Grammars and Language Models for Automatic Speech Recognition
Beneš, Karel ; Glembek, Ondřej (referee) ; Hannemann, Mirko (advisor)
Tato práce se zabývá transformací bezkontextových gramatik na váhované konečně stavové převodníky. Je vybrána podmnožina bezkontextových gramatik, kterou lze tranformovat přesně. Je představen test, zda daná gramatika naleží do této podmnožiny, i algoritmus převodu. Dále je popsán vlastní nástroj, který tyto postupy implementuje, včetně způsobu zpracování vstupu a výstupu. S použitím toho nástroje byl vytvořen systém rozpoznání řeči pro kokpit letadla. Jsou představeny výsledky ukazující, že systém založený na takto získaném modelu jazyka podává výrazně lepší výkon, než je dosažen při použití obecného modelu.
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Gaze-Based Keyboard
Sznapka, Jakub ; Herout, Adam (referee) ; Hradiš, Michal (advisor)
The goal of this bachelor's thesis is to create a tool for gaze typing. It deals with gaze tracking and evalution issues. It contains a description of the Swype method which is used for typing on touch screen devices. Then follows the analysis of different ways which could be used to model the language used by model. The main part is dedicated to design of the gaze typing tool and implementation using the Kaldi toolkit.
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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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Reordering Text Fragments Using a Language Model
Holubec, Michael ; Kocour, Martin (referee) ; Beneš, Karel (advisor)
The aim of this work is to construct and experimentally verify the effectiveness of the language model in identifying the reading order. For this purpose language model with LSTM architecture was constructed. This work designs and implements three methods which are used to identify reading order. These methods are Language analysis, Spatial analysis and Combined analysis. Language analysis and combined analysis used constructed language model. The success of the language model, and all three methods, was measured on three datasets containing newspaper articles. Language analysis reaches 57,6 % and spatial analysis reaches 91,6 %. Combined analysis achieved the best results 92,9 %. The work shows that the language model can be used to identify reading order but use of additional data (e.g. spatial data
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Domain Specific Data Crawling for Language Model Adaptation
Gregušová, Sabína ; Švec, Ján (referee) ; Karafiát, Martin (advisor)
The goal of this thesis is to implement a system for automatic language model adaptation for Phonexia ASR system. System expects input in the form of source that, which is analysed and appropriate terms for web search are chosen. Every web search results in a set of documents that undergo cleaning and filtering procedures. The resulting web corpora is mixed with Phonexia model and evaluated. In order to estimate the most optimal parameters, I conducted 3 sets of experiments for Hindi, Czech and Mandarin. The results of the experiments were very favourable and the implemented system managed to decrease perplexity and Word Error Rate in most cases.
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Mining of Textual Data from the Web for Speech Recognition
Kubalík, Jakub ; Plchot, Oldřich (referee) ; Mikolov, Tomáš (advisor)
Prvotním cílem tohoto projektu bylo prostudovat problematiku jazykového modelování pro rozpoznávání řeči a techniky pro získávání textových dat z Webu. Text představuje základní techniky rozpoznávání řeči a detailněji popisuje jazykové modely založené na statistických metodách. Zvláště se práce zabývá kriterii pro vyhodnocení kvality jazykových modelů a systémů pro rozpoznávání řeči. Text dále popisuje modely a techniky dolování dat, zvláště vyhledávání informací. Dále jsou představeny problémy spojené se získávání dat z webu, a v kontrastu s tím je představen vyhledávač Google. Součástí projektu byl návrh a implementace systému pro získávání textu z webu, jehož detailnímu popisu je věnována náležitá pozornost. Nicméně, hlavním cílem práce bylo ověřit, zda data získaná z Webu mohou mít nějaký přínos pro rozpoznávání řeči. Popsané techniky se tak snaží najít optimální způsob, jak data získaná z Webu použít pro zlepšení ukázkových jazykových modelů, ale i modelů nasazených v reálných rozpoznávacích systémech.
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