Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference?
| Autor: | Alina Karakanta, Marco Gaido, Luisa Bentivogli, Alberto Martinelli, Mauro Cettolo, Matteo Negri, Marco Turchi |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Computation and Language business.industry Computer science Performance gap Mathematical proof Translation (geometry) computer.software_genre Cascade Direct speech Speech translation Artificial intelligence business Computation and Language (cs.CL) computer Natural language processing |
| Zdroj: | ACL/IJCNLP (1) Scopus-Elsevier Università degli di Trento-IRIS |
| Popis: | Five years after the first published proofs of concept, direct approaches to speech translation (ST) are now competing with traditional cascade solutions. In light of this steady progress, can we claim that the performance gap between the two is closed? Starting from this question, we present a systematic comparison between state-of-the-art systems representative of the two paradigms. Focusing on three language directions (English-German/Italian/Spanish), we conduct automatic and manual evaluations, exploiting high-quality professional post-edits and annotations. Our multi-faceted analysis on one of the few publicly available ST benchmarks attests for the first time that: i) the gap between the two paradigms is now closed, and ii) the subtle differences observed in their behavior are not sufficient for humans neither to distinguish them nor to prefer one over the other. Comment: Accepted at ACL2021 |
| Databáze: | OpenAIRE |
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