Aim, of this master thesis is training of phoneme recognizer with phoneme set, which have been made by merging of several phoneme sets, which are containted in SpeechDat-E database and find out if this kind of recognizer will have better results than recognizers which were trained on one language. This work also deals with phoneme sets, principles of phoneme recognition using recognizers based on artifical neural networks, language identification and merging of given phoneme sets. Also is described process of training phoneme recognizer and phoneme recognition.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:235509 |
| Creators | Vobr, Vojtěch |
| Contributors | Matějka, Pavel, Szőke, Igor |
| 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 |
Page generated in 0.0018 seconds