| Paper ID | SPE-46.3 |
| Paper Title |
MULTILINGUAL PHONETIC DATASET FOR LOW RESOURCE SPEECH RECOGNITION |
| Authors |
Xinjian Li, David Mortensen, Florian Metze, Alan Black, Carnegie Mellon University, United States |
| Session | SPE-46: Corpora and Other Resources |
| Location | Gather.Town |
| Session Time: | Thursday, 10 June, 16:30 - 17:15 |
| Presentation Time: | Thursday, 10 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Speech Processing: [SPE-GASR] General Topics in Speech Recognition |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
Phone Recognition is one of the most important tasks in the field of multilingual speech recognition, especially for low-resource languages whose orthographies are not available. However, most speech recognition datasets so far only focus on high-resource languages, there are very few datasets available for low-resource languages, especially datasets with detailed phone annotation. In this work, we present a large multilingual phonetic dataset, which is preprocessed and aligned from the UCLA phonetic dataset. The dataset contains around 100 low-resource languages and 7000 utterances in total. This dataset would provide an ideal training/evaluation set for universal phone recognition. |
