Papers by Sheila Castilho
Improving Machine Translation of Educational Content via Crowdsourcing (L18-1)
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Maximiliana Behnke, Antonio Valerio Miceli Barone, Rico Sennrich, Vilelmini Sosoni, Thanasis Naskos, Eirini Takoulidou, Maria Stasimioti, Menno van Zaanen, Sheila Castilho, Federico Gaspari, Panayota Georgakopoulou, Valia Kordoni, Markus Egg, Katia Lida Kermanidis
| Challenge: | Using crowdsourcing to train neural machine translation models is expensive and expensive . professional outsourcing of bilingual data is expensive if the translations are of a lower quality . |
| Approach: | They analyze the impact of crowdsourcing on the quality of in-domain training data . they use translations of MOOCs from English to eleven languages to fine-tune machine translation models . |
| Outcome: | The proposed method improves on general-domain training data and with pre-existing in-domain corpora. |
Translation Crowdsourcing: Creating a Multilingual Corpus of Online Educational Content (L18-1)
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Vilelmini Sosoni, Katia Lida Kermanidis, Maria Stasimioti, Thanasis Naskos, Eirini Takoulidou, Menno van Zaanen, Sheila Castilho, Panayota Georgakopoulou, Valia Kordoni, Markus Egg
| Challenge: | a large corpus of online content has been developed via large-scale crowdsourcing. |
| Approach: | They describe a multilingual corpus of online content that has been manually translated into 11 European and BRIC languages using the crowdsourcing platform. |
| Outcome: | The proposed corpus is a product of the EU-funded TraMOOC project and is used to train, tune and test machine translation engines. |
How Much Context Span is Enough? Examining Context-Related Issues for Document-level MT (2022.lrec-1)
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| Challenge: | Recent advances in neural machine translation (NMT) have made it possible to include discourse into translation systems. |
| Approach: | They use the DELA corpus to examine the context span needed to translate from English into Portuguese. |
| Outcome: | The shortest span to disambiguate issues can appear in different positions in the document including preceding, following, global, world knowledge. |
On Context Span Needed for Machine Translation Evaluation (2020.lrec-1)
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| Challenge: | a number of common patterns can be observed for context-aware MT evaluation, authors say . document-level evaluations have largely been performed at the sentence level . the definition of what constitutes a "document level" evaluation is still unclear . |
| Approach: | They propose to use a series of surveys to identify the necessary context span . they find common patterns that can be used to draw general guidelines . |
| Outcome: | The proposed evaluations of machine translation systems show that some issues and spans depend on domain and target language. |