Abstract
We present a new freely available corpus for German distant speech recognition and report speaker-independent word error rate (WER) results for two open source speech recognizers trained on this corpus. The corpus has been recorded in a controlled environment with three different microphones at a distance of one meter. It comprises 180 different speakers with a total of 36 hours of audio recordings. We show recognition results with the open source toolkit Kaldi (20.5% WER) and PocketSphinx (39.6% WER) and make a complete open source solution for German distant speech recognition possible.
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Radeck-Arneth, S., Milde, B., Lange, A., Gouvêa, E., Radomski, S., Mühlhäuser, M., & Biemann, C. (2015). Open source German distant speech recognition: Corpus and acoustic model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9302, pp. 480–488). Springer Verlag. https://doi.org/10.1007/978-3-319-24033-6_54
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