2020/10/06 by Michel Plüss, Plüss, Michel, Lukas Neukom +5 · 3 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Speech Recognition and Synthesis #Speech and dialogue systems #cs.CL #cs.LG
paper · pdf · doi:10.48550/arxiv.2010.02810
8 pages, 0 figures
openalex publication_date 2020/10/06 · arxiv created 2021/06/09 · arxiv updated 2021/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present the Swiss Parliaments Corpus (SPC), an automatically aligned Swiss German speech to Standard German text corpus. This first version of the corpus is based on publicly available data of the Bernese cantonal parliament and consists of 293 hours of data. It was created using a novel forced sentence alignment procedure and an alignment quality estimator, which can be used to trade off corpus size and quality. We trained Automatic Speech Recognition (ASR) models as baselines on different subsets of the data and achieved a Word Error Rate (WER) of 0.278 and a BLEU score of 0.586 on the SPC test set. The corpus is freely available for download.