ASR Bundestag: A large-scale political debate dataset in German.
Abstract
We present ASR Bundestag, a dataset for automatic speech recognition in German, consisting of 610 hours of aligned audio-transcript pairs for supervised training as well as 1,038 hours of unlabeled audio snippets for self-
supervised learning, based on raw audio data and transcriptions from plenary sessions and committee meetings of the German parliament. In addition, we discuss utilized approaches for the automated creation of speech datasets and assess the quality of the resulting dataset based on evaluations and finetuning of a pre-trained state of the art model. We make the dataset publicly available, including all subsets.
Mehr zum Titel
| Titel | ASR Bundestag: A large-scale political debate dataset in German. |
|---|---|
| Medien | Proceedings of SAI Intelligent Systems Conference (pp. 190-202) |
| Verlag | Springer Nature Switzerland. |
| Verfasser | Johannes Wirth, Prof. Dr. René Peinl |
| Veröffentlichungsdatum | 01.07.2023 |
| Zitation | Wirth, Johannes; Peinl, René (2023): ASR Bundestag: A large-scale political debate dataset in German.. Proceedings of SAI Intelligent Systems Conference (pp. 190-202). |