2015 | OriginalPaper | Buchkapitel
Open Source German Distant Speech Recognition: Corpus and Acoustic Model
verfasst von : Stephan Radeck-Arneth, Benjamin Milde, Arvid Lange, Evandro Gouvêa, Stefan Radomski, Max Mühlhäuser, Chris Biemann
Erschienen in: Text, Speech, and Dialogue
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.