Pronounciation analysis and mispronounciation detection
| dc.contributor.author | Omar A. | |
| dc.date.accessioned | 2024-12-17T06:25:40Z | |
| dc.date.available | 2024-12-17T06:25:40Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | We are interested in developing software that can automatically recognize particular phone segments that a non-native student of a foreign language has pronounced incorrectly. A language training system can provide the student with feedback about individual pronunciation errors by using the information about the phone level. For this purpose, in this work, I am trying to develop a transformer model that will recognize spell errors in speech. There were two strategies that were examined: the first one on the original audio dataset, and the second one on the synthetically augmented dataset. Both experiments were compared in this work. | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1580 | |
| dc.language.iso | en | |
| dc.subject | software, phone, segments, a non-native student, foreign language, dataset | |
| dc.title | Pronounciation analysis and mispronounciation detection | |
| dc.type | Other |