Code-Switching Speech Corpus

German-English Code-Switching speech dataset We provide means to resegment a subset of the German **Spoken Wikipedia Corpus** (SWC) enabling a particular focus on code-switching. This results in the German-English code-switching corpus, a 34h transcribed speech corpus of read Wikipedia articles which can be used as a benchmark for research on code-switching. The articles are read by a large and diverse group of people. The SWC is perhaps the largest corpus of freely-available aligned speech for German. It contains 1014 spoken articles read by more than 350 identified speakers comprising 386h of speech. This corpus is available at http://nats.gitlab.io/swc. In SWC, since most of the articles are long, the recordings submitted by the volunteers are also long (∼54min) on average. These audio files are manually annotated at word-level and also segment level in XML format. We use a language identification tool to detect code-switching in the transcription of the audio files with consecutive indices. To extract intra-sentential code-switching segments, we ensure that the detected code-switching is preceded and followed by German words or sentences. The final set consists of 34h of speech data and 12,437 code-switching segments (in Kaldi ASR toolkit data format). Citation @article{baumann2019spoken, title={The Spoken Wikipedia Corpus collection: Harvesting, alignment and an application to hyperlistening}, author={Baumann, Timo and K{\"o}hn, Arne and Hennig, Felix}, journal={Language Resources and Evaluation}, volume={53}, number={2}, pages={303--329}, year={2019}, publisher={Springer} } @article{grave2018learning, title={Learning word vectors for 157 languages}, author={Grave, Edouard and Bojanowski, Piotr and Gupta, Prakhar and Joulin, Armand and Mikolov, Tomas}, journal={arXiv preprint arXiv:1802.06893}, year={2018} }