The Multilingual TEDx Corpus for Speech Recognition and Translation
| Autor: | Matthew Wiesner, Jacob Bremerman, Marco Turchi, Matt Post, Elizabeth Salesky, Matteo Negri, Roldano Cattoni, Douglas W. Oard |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Computation and Language Computer science Speech translation Speech recognition InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Translation (geometry) Computation and Language (cs.CL) ComputingMethodologies_ARTIFICIALINTELLIGENCE Code (semiotics) |
| Zdroj: | Interspeech 2021. |
| Popis: | 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. Accepted to Interspeech 2021 |
| Databáze: | OpenAIRE |
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