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Detection of selected audio events in a real environment
Kowolowski, Alexander ; Burget, Radim (referee) ; Přinosil, Jiří (advisor)
This work deals with methods for the detection of dangerous events, in this case gunshots, in a real environment. First of all, a testing and training database of sounds from the MIVIA database was created. In this database, the files were contained in six versions of signal-to-noise ratio, so the subsequent testing of the selected methods took place for the various shuffled files, and it was found that some methods are more accurate for cleaner recordings than others, but less accurate for more noisy ones. For the typical feature extraction from the input sound, the mel-frequency cepstral coefficients method was always used. In the thesis, the methods of support vector machines and ensemble of a number of weak classifiers are gradually tested on the created databases. These methods are then further optimized, for example by using statistical variables, and after optimization they achieve better results, as expected. In the work, two scripts were created, where one created a training database and on this data trained the classifier and the other created the test database, tested the selected classifier and obtained the results. The results are processed by confusion matrix and several proportional variables such as accuracy, sensitivity, specificity and others are calculated. These results are always listed in the relevant chapter of the thesis in the tables and column charts and are properly commented on.
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Automatic Recognition of Logopaedic Defect in Speech Utterances
Dušil, Lubomír ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The thesis is aimed at an analysis and automatic detection of logopaedic defects in speech utterance. Its objective is to facilitate and accelerate the work of logopaedists and to increase percentage of detected logopaedic defects in children of the youngest possible age followed by the most successful treatment. It presents methods of speech work, classification of the defects within individual stages of child development and appropriate words for identification of the speech defects and their subsequent remedy. After that there are analyses of methods of calculating coefficients which reflect human speech best. Also classifiers which are used to discern and determine whether it is a speech defect or not. Classifiers exploit coefficients for their work. Coefficients and classifiers are being tested and their best combination is being looked for in order to achieve the highest possible success rate of the automatic detection of the speech defects. All the programming and testing jobs has been conducted in the Matlab programme.
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Detection of selected audio events in a real environment
Kowolowski, Alexander ; Burget, Radim (referee) ; Přinosil, Jiří (advisor)
This work deals with methods for the detection of dangerous events, in this case gunshots, in a real environment. First of all, a testing and training database of sounds from the MIVIA database was created. In this database, the files were contained in six versions of signal-to-noise ratio, so the subsequent testing of the selected methods took place for the various shuffled files, and it was found that some methods are more accurate for cleaner recordings than others, but less accurate for more noisy ones. For the typical feature extraction from the input sound, the mel-frequency cepstral coefficients method was always used. In the thesis, the methods of support vector machines and ensemble of a number of weak classifiers are gradually tested on the created databases. These methods are then further optimized, for example by using statistical variables, and after optimization they achieve better results, as expected. In the work, two scripts were created, where one created a training database and on this data trained the classifier and the other created the test database, tested the selected classifier and obtained the results. The results are processed by confusion matrix and several proportional variables such as accuracy, sensitivity, specificity and others are calculated. These results are always listed in the relevant chapter of the thesis in the tables and column charts and are properly commented on.
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Automatic Recognition of Logopaedic Defect in Speech Utterances
Dušil, Lubomír ; Atassi, Hicham (referee) ; Smékal, Zdeněk (advisor)
The thesis is aimed at an analysis and automatic detection of logopaedic defects in speech utterance. Its objective is to facilitate and accelerate the work of logopaedists and to increase percentage of detected logopaedic defects in children of the youngest possible age followed by the most successful treatment. It presents methods of speech work, classification of the defects within individual stages of child development and appropriate words for identification of the speech defects and their subsequent remedy. After that there are analyses of methods of calculating coefficients which reflect human speech best. Also classifiers which are used to discern and determine whether it is a speech defect or not. Classifiers exploit coefficients for their work. Coefficients and classifiers are being tested and their best combination is being looked for in order to achieve the highest possible success rate of the automatic detection of the speech defects. All the programming and testing jobs has been conducted in the Matlab programme.
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