This master's thesis deals with code-switching detection in speech. The state-of-the-art methods of language diarization are described in the first part of the thesis. The proposed method for implementation is based on acoustic approach to language identification using combination of GMM, i-vector and LDA. New Mandarin-English code-switching database was created for these experiments. Using this system, accuracy of 89,3 % is achieved on this database.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:234890 |
| Date | January 2015 |
| Creators | Povolný, Filip |
| 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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