|Elizabeth Salesky (Johns Hopkins University, USA), Matthew Wiesner (Johns Hopkins University, USA), Jacob Bremerman (University of Maryland, USA), Roldano Cattoni (FBK, Italy), Matteo Negri (FBK, Italy), Marco Turchi (FBK, Italy), Douglas W. Oard (University of Maryland, USA), Matt Post (Johns Hopkins University, USA)|
We present the Multilingual TEDx corpus, built to support speech recognition (ASR) and speech translation (ST) research across many non-English source languages. The corpus is a collection of audio recordings from TEDx talks in 8 source languages. We segment transcripts into sentences and align them to the source-language audio and target-language translations. The corpus is released along with open-sourced code enabling extension to new talks and languages as they become available. Our corpus creation methodology can be applied to more languages than previous work, and creates multi-way parallel evaluation sets. We provide baselines in multiple ASR and ST settings, including multilingual models to improve translation performance for low-resource language pairs.