Zobrazeno 1 - 10
of 113
pro vyhledávání: '"Tsiamas, P."'
Video-to-audio (V2A) generation leverages visual-only video features to render plausible sounds that match the scene. Importantly, the generated sound onsets should match the visual actions that are aligned with them, otherwise unnatural synchronizat
Externí odkaz:
http://arxiv.org/abs/2407.10387
Contrastive learning has emerged as a powerful technique in audio-visual representation learning, leveraging the natural co-occurrence of audio and visual modalities in extensive web-scale video datasets to achieve significant advancements. However,
Externí odkaz:
http://arxiv.org/abs/2407.05782
Data scarcity and the modality gap between the speech and text modalities are two major obstacles of end-to-end Speech Translation (ST) systems, thus hindering their performance. Prior work has attempted to mitigate these challenges by leveraging ext
Externí odkaz:
http://arxiv.org/abs/2402.10422
This paper describes the submission of the UPC Machine Translation group to the IWSLT 2023 Offline Speech Translation task. Our Speech Translation systems utilize foundation models for speech (wav2vec 2.0) and text (mBART50). We incorporate a Siamese
Externí odkaz:
http://arxiv.org/abs/2306.01327
Language Generation Models produce words based on the previous context. Although existing methods offer input attributions as explanations for a model's prediction, it is still unclear how prior words affect the model's decision throughout the layers
Externí odkaz:
http://arxiv.org/abs/2305.12535
End-to-end Speech Translation is hindered by a lack of available data resources. While most of them are based on documents, a sentence-level version is available, which is however single and static, potentially impeding the usefulness of the data. We
Externí odkaz:
http://arxiv.org/abs/2212.09699
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 o
Externí odkaz:
http://arxiv.org/abs/2210.16264
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 real-world scenario
Externí odkaz:
http://arxiv.org/abs/2202.04774
Autor:
Gállego, Gerard I., Tsiamas, Ioannis, Escolano, Carlos, Fonollosa, José A. R., Costa-jussà, Marta R.
This paper describes the submission to the IWSLT 2021 offline speech translation task by the UPC Machine Translation group. The task consists of building a system capable of translating English audio recordings extracted from TED talks into German te
Externí odkaz:
http://arxiv.org/abs/2105.04512
Autor:
Tsiamas, P., Sajo, E., Cifter, F., Theodorou, K., Kappas, C., Makrigiorgos, M., Marcus, K., Zygmanski, P.
Publikováno v:
In Physica Medica February 2014 30(1):47-56