José A. R. Fonollosa
5 papers in the PaperMetrix corpus
Papers by this author
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(Self-Attentive) Autoencoder-based Universal Language Representation for Machine Translation
2018 · arXiv (Cornell University)
Universal language representation is the holy grail in machine translation (MT). Thanks to the new neural MT approach, it seems that there are good perspectives towards this goal. In this paper, we propose a new …
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From bilingual to multilingual neural‐based machine translation by incremental training
2020 · Journal of the Association for Information Science and Technology
Abstract A common intermediate language representation in neural machine translation can be used to extend bilingual systems by incremental training. We propose a new architecture based on introducing an interlingual loss as an additional training …
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SHAS: Approaching optimal Segmentation for End-to-End Speech Translation
2022 · arXiv (Cornell University)
Speech translation models are unable to directly process long audios, like TED talks, which have to be split into shorter segments. Speech translation datasets provide manual segmentations of the audios, which are not available in …
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Efficient Speech Translation with Dynamic Latent Perceivers
2023
Transformers have been the dominant architecture for Speech Translation in recent years, achieving significant improvements in translation quality. Since speech signals are longer than their textual counterparts, and due to the quadratic complexity of the …
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Character-based neural machine translation
2016 · UPCommons institutional repository (Universitat Politècnica de Catalunya)
Neural Machine Translation (MT) has reached state-of-the-art results. However, one of the main challenges that neural MT still faces is dealing with very large vocabularies and morphologically rich languages. In this paper, we propose a …