The topic of this thesis is an audio recording classification with 15 different acoustic scene classes that represent common scenes and places where people are situated on a regular basis. The thesis describes 2 approaches based on GMM and i-vectors and a fusion of the both approaches. The score of the best GMM system which was evaluated on the evaluation dataset of the DCASE Challenge is 60.4%. The best i-vector system's score is 68.4%. The fusion of the GMM system and the best i-vector system achieves score of 69.3%, which would lead to the 20th place in the all systems ranking of the DCASE 2017 Challenge (among 98 submitted systems from all over the world).
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:385945 |
Date | January 2018 |
Creators | Dobrotka, Matúš |
Contributors | Glembek, Ondřej, Matějka, Pavel |
Publisher | Vysoké učení technické v Brně. Fakulta informačních technologií |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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