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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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Searching Acoustic Patterns in Speech Data without Recognition
Skácel, Miroslav ; Fapšo, Michal (referee) ; Černocký, Jan (advisor)
This work investigates into methods for words, word phrases and longer segments detection in large speech data sets in an unsupervised way. At first, basics for the given topic and principles of modern methods for searching of repeating objects are introduced. The representation and segmentation of the input data are described. Techniques for object detection in speech are presented. The description of found motifs modelling follows. The next step defi nes data sets for experiments in which spoken term detection by an example is performed. The system requirements are described. In the conclusion, the work is summarised and suggestions for further development are discussed.
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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.
|
|
|
Searching Acoustic Patterns in Speech Data without Recognition
Skácel, Miroslav ; Fapšo, Michal (referee) ; Černocký, Jan (advisor)
This work investigates into methods for words, word phrases and longer segments detection in large speech data sets in an unsupervised way. At first, basics for the given topic and principles of modern methods for searching of repeating objects are introduced. The representation and segmentation of the input data are described. Techniques for object detection in speech are presented. The description of found motifs modelling follows. The next step defi nes data sets for experiments in which spoken term detection by an example is performed. The system requirements are described. In the conclusion, the work is summarised and suggestions for further development are discussed.
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