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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Acoustic Scene Classification from Speech
 Grepl, Filip ; Beneš, Karel (referee) ; Matějka, Pavel (advisor)
This thesis deals with creating a system whose task is to recognize what type of location the recording was created at by analyzing the audio signal. The classifier is based on a multi-layer, fully connected neural network. The topology of the neural network is based on the baseline system provided for the DCASE competition. A dataset from this competition is also used for training and evaluating the neural network. The experiments are performed in particular with the representation of the properties of the audio records and with the format of the input data of the neural network. For this purpose, Mel-filter bank, block Mel-filter bank and MFCC flags are used. The experiments performed in this thesis brought a classification accuracy increased by 6.5 % compared to the baseline system of DCASE. Overall system success rate reached 67.5 %.
Detailed record
Acoustic Scene Classification from Speech
 Grepl, Filip ; Beneš, Karel (referee) ; Matějka, Pavel (advisor)
This thesis deals with creating a system whose task is to recognize what type of location the recording was created at by analyzing the audio signal. The classifier is based on a multi-layer, fully connected neural network. The topology of the neural network is based on the baseline system provided for the DCASE competition. A dataset from this competition is also used for training and evaluating the neural network. The experiments are performed in particular with the representation of the properties of the audio records and with the format of the input data of the neural network. For this purpose, Mel-filter bank, block Mel-filter bank and MFCC flags are used. The experiments performed in this thesis brought a classification accuracy increased by 6.5 % compared to the baseline system of DCASE. Overall system success rate reached 67.5 %.
Detailed record

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