Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation
Speech translation has traditionally been approached through cascaded models consisting of a speech recognizer trained on a corpus of transcribed speech, and a machine translation system trained on parallel texts. Several recent works have shown the feasibility of collapsing th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
The MIT Press
2019-11-01
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| Series: | Transactions of the Association for Computational Linguistics |
| Online Access: | https://www.mitpressjournals.org/doi/abs/10.1162/tacl_a_00270 |