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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6...105 Hits 21 – 40 of 2.082 21 Attitudes towards the collection and linkage of maltreatment data for research: A qualitative study Moody, Gwenllian; Cannings-John, Rebecca; Hood, Kerenza... In: Int J Popul Data Sci (2022) BASE Show details 22 LIMSI @ WMT’14 Medical Translation Task Yvon, François; Do, Quoc Khanh; Lavergne, Thomas. - : Association for Computational Linguistics, 2022 BASE Show details 23 Maastricht University’s Multilingual Speech Translation System for IWSLT 2021 Liu, Danni; Niehues, Jan. - : Association for Computational Linguistics, 2022 BASE Show details 24 Findings of the IWSLT 2020 Evaluation campaign Niehues, Jan; Federico, Marcello; Ma, Xutai. - : Association for Computational Linguistics, 2022 BASE Show details 25 Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder Ha, Thanh-Le; Niehues, Jan; Waibel, Alex. - 2022 BASE Show details 26 The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2017 Waibel, Alexander; Ha, Thanh-Le; Sperber, Matthias. - : Association for Computational Linguistics, 2022 BASE Show details 27 Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation Neubig, Graham; Sperber, Matthias; Waibel, Alex; Niehues, Jan In: Transactions of the Association for Computational Linguistics, 7, 313–325 ; ISSN: 2307-387X (2022) Abstract: 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 the cascade into a single, direct model that can be trained in an end-to-end fashion on a corpus of translated speech. However, experiments are inconclusive on whether the cascade or the direct model is stronger, and have only been conducted under the unrealistic assumption that both are trained on equal amounts of data, ignoring other available speech recognition and machine translation corpora. In this paper, we demonstrate that direct speech translation models require more data to perform well than cascaded models, and although they allow including auxiliary data through multi-task training, they are poor at exploiting such data, putting them at a severe disadvantage. As a remedy, we propose the use of end-to-end trainable models with two attention mechanisms, the first establishing source speech to source text alignments, the second modeling source to target text alignment. We show that such models naturally decompose into multi-task–trainable recognition and translation tasks and propose an attention-passing technique that alleviates error propagation issues in a previous formulation of a model with two attention stages. Our proposed model outper-forms all examined baselines and is able to exploit auxiliary training data much more effectively than direct attentional models. Keyword: DATA processing & computer science; ddc:004; info:eu-repo/classification/ddc/004 URL: https://publikationen.bibliothek.kit.edu/1000145064 https://publikationen.bibliothek.kit.edu/1000145064/148663710 https://doi.org/10.5445/IR/1000145064 BASE Hide details 28 Analyzing Neural MT Search and Model Performance Waibel, Alex; Niehues, Jan; Cho, Eunah. - : Association for Computational Linguistics, 2022 BASE Show details 29 Joint WMT 2012 Submission of the QUAERO Project Le, Hai-son; Lavergne, Thomas; Freitag, Markus. - : Association for Computational Linguistics, 2022 BASE Show details 30 Adapting End-to-End Speech Recognition for Readable Subtitles Spanakis, Gerasimos; Liu, Danni; Niehues, Jan. - : Association for Computational Linguistics, 2022 BASE Show details 31 Inspection of Multilingual Neural Machine Translation Mullov, Carlos; Niehues, Jan; Waibel, Alex. - 2022 BASE Show details 32 KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning Nguyen, Thai-Son; Zenkel, Thomas; Waibel, Alex. - : Association for Computational Linguistics, 2022 BASE Show details 33 The Karlsruhe Institute of Technology Translation Systems for the WMT 2012 Herrmann, T.; Zhang, Y.; Waibel, A.. - : Association for Computational Linguistics, 2022 BASE Show details 34 Robust and Scalable Differentiable Neural Computer for Question Answering Niehues, Jan; Franke, Jörg; Waibel, Alex. - : Association for Computational Linguistics, 2022 BASE Show details 35 Lecture Translator Speech translation framework for simultaneous lecture translation Waibel, Alex; Nguyen, Thai-Son; Cho, Eunah. - : Association for Computational Linguistics, 2022 BASE Show details 36 The Universität Karlsruhe Translation System for the EACL-WMT 2009 Herrmann, Teresa; Waibel, Alex; Kolss, Muntsin. - : Association for Computational Linguistics, 2022 BASE Show details 37 Tutorial: End-to-End Speech Translation Negri, Matteo; Salesky, Elizabeth; Turchi, Marco. - : Association for Computational Linguistics, 2022 BASE Show details 38 Incremental processing of noisy user utterances in the spoken language understanding task Constantin, Stefan; Niehues, Jan; Waibel, Alex. - : Association for Computational Linguistics, 2022 BASE Show details 39 Improving Zero-shot Translation with Language-Independent Constraints Niehues, Jan; Pham, Ngoc-Quan; Waibel, Alex. - : Association for Computational Linguistics, 2022 BASE Show details 40 Lexical Translation Model Using A Deep Neural Network Architecture Ha, Thanh-Le; Niehues, Jan; Waibel, Alex. - 2022 BASE Show details Page: 1 2 3 4 5 6...105

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