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Vizualization of Outputs from Speech Technologies for Contact Centers
Zhezhela, Oleksandr ; Szőke, Igor (referee) ; Schwarz, Petr (advisor)
The thesis is aimed on visualisation of data mined by speech processing technologies. Some methods speech data extraction were studied and technologies for this task were analysed. The variety of meta data that can be mined from speech was defined. Were also examined existing standards and processes of call centres. Some requirements for the user interface were gathered and analysed. On that basis and after communication with call centre employees there was defined and implemented a concept for speech data visualization. Gained solutions were integrated into Speech Analytics Server (SPAS).
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Estimation of accuracy of speech technologies based on signal quality and audio content richness
Nezval, Jiří ; Smital, Lukáš (referee) ; Schwarz, Petr (advisor)
This thesis discusses theoretical analysis of the origin of speech, introduces applications of speech technologies and explains the contemporary approach to phonetical transcription of speech recordings. Furthermore, it describes the metrics of audio recordings quality assessment, which is split into two discrete classes. The first one groups signal quality metrics, while the other one groups content richness metrics. The first goal of the practical section is to create a statistical model for accuracy prediction of machine transcription of speech recordings based on a measurement of their quality. The second goal is to evaluate which partial metrics are the most essential for accuracy prediction of machine transcription.
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Topic Detection from Spoken Speech
Škeřík, Zdeněk ; Szőke, Igor (referee) ; Schwarz, Petr (advisor)
This thesis is about topic detection from spoken speech. The first part of the thesis deals with speech transcription to text. The thesis describes two different solutions of the topic detection - a machine learning based solution and an expert solution that composes a very precise query describing the document topic. Both methods are tested on a set of recordings and compared.
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Estimation of accuracy of speech technologies based on signal quality and audio content richness
Nezval, Jiří ; Smital, Lukáš (referee) ; Schwarz, Petr (advisor)
This thesis discusses theoretical analysis of the origin of speech, introduces applications of speech technologies and explains the contemporary approach to phonetical transcription of speech recordings. Furthermore, it describes the metrics of audio recordings quality assessment, which is split into two discrete classes. The first one groups signal quality metrics, while the other one groups content richness metrics. The first goal of the practical section is to create a statistical model for accuracy prediction of machine transcription of speech recordings based on a measurement of their quality. The second goal is to evaluate which partial metrics are the most essential for accuracy prediction of machine transcription.
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Vizualization of Outputs from Speech Technologies for Contact Centers
Zhezhela, Oleksandr ; Szőke, Igor (referee) ; Schwarz, Petr (advisor)
The thesis is aimed on visualisation of data mined by speech processing technologies. Some methods speech data extraction were studied and technologies for this task were analysed. The variety of meta data that can be mined from speech was defined. Were also examined existing standards and processes of call centres. Some requirements for the user interface were gathered and analysed. On that basis and after communication with call centre employees there was defined and implemented a concept for speech data visualization. Gained solutions were integrated into Speech Analytics Server (SPAS).
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Topic Detection from Spoken Speech
Škeřík, Zdeněk ; Szőke, Igor (referee) ; Schwarz, Petr (advisor)
This thesis is about topic detection from spoken speech. The first part of the thesis deals with speech transcription to text. The thesis describes two different solutions of the topic detection - a machine learning based solution and an expert solution that composes a very precise query describing the document topic. Both methods are tested on a set of recordings and compared.
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