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National Repository of Grey Literature 3 records found  Search took 0.00 seconds. 
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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Ppg Signal Quality Assessment And Heart Rate Estimation
 Vargová, Enikö
The presented paper describes an algorithm for signal quality assessment based on clusteranalysis and also an algorithm for heart rate estimation from PPG signals. This work includesa database which comprises 48 PPG signals collected by a smartphone and 48 ECG signals recordedby an ECG recorder. The accuracy of the quality assessment is 97,5 % on the training set and87,5 % on the test set. The average deviation of the estimated heart rate is 1,39889 bpm.
Detailed record
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.
Detailed record

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