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Transcription and annotation components for web editor in React
Dugovič, Jakub ; Herout, Adam (referee) ; Szőke, Igor (advisor)
Cieľom tejto práci je implementovať modulárne užívateľské rozhranie na prepis zvukových nahrávok a ich anotáciu. Rozširuje dotrajšiu prácu s cieľom umožniť a zjednodušiť prácu s hodiny dlhými nahrávkami rozhovorov. Riešenie je implementované v TypeScripte pomocou Reactu a ďalších knižníc z reactového ekosystému. Aplikujúc princípy naštudované z literatúry, vyhýbajúc sa chybám identifikovaným počas prieskumu obdobnej platformy a overujúc užívateľské rozhranie počas vývoja pomocou kvalitatívneho testovania, vyvýjané rozhranie sa usiluje dosiahnuť vysokú mieru dobrej užívateľskej skúsenosti.
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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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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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