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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 Hits 1 – 20 of 53 1 Findings of the IWSLT 2020 Evaluation campaign Niehues, Jan; Federico, Marcello; Ma, Xutai. - : Association for Computational Linguistics, 2022 BASE Show details 2 MeetDot: Videoconferencing with Live Translation Captions ... Arkhangorodsky, Arkady; Chu, Christopher; Fang, Scot. - : arXiv, 2021 BASE Show details 3 MeetDot: Videoconferencing with Live Translation Captions ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Arkhangorodsky, Arkady; Chu, Christopher. - : Underline Science Inc., 2021 BASE Show details 4 Abstract Meaning Representation (AMR) Annotation Release 3.0 Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2020. : https://www.ldc.upenn.edu, 2020 BASE Show details 5 Parallel Corpus Filtering via Pre-trained Language Models ... Zhang, Boliang; Nagesh, Ajay; Knight, Kevin. - : arXiv, 2020 BASE Show details 6 Findings of the IWSLT 2020 Evaluation campaign ... Ansari, Ebrahim; Axelrod, Amittai; Bach, Nguyen. - : Association for Computational Linguistics, 2020 BASE Show details 7 Abstract Meaning Representation (AMR) Annotation Release 3.0 ... Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2020 BASE Show details 8 Learning to Pronounce Chinese Without a Pronunciation Dictionary ... Chu, Christopher; Fang, Scot; Knight, Kevin. - : arXiv, 2020 BASE Show details 9 Cross-lingual entity extraction and linking for 300 languages Pan, Xiaoman. - 2020 Abstract: Information provided in languages that people can understand saves lives in crises. For example, the language barrier was one of the main difficulties faced by humanitarian workers responding to the Ebola crisis in 2014. We propose to break language barriers by extracting information (e.g., entities) from a massive variety of languages and ground the information into an existing Knowledge Base (KB) which is accessible to a user in their own language (e.g., a reporter from the World Health Organization who speaks English only). The ambitious goal of this thesis is to develop a Cross-lingual Entity Extraction and Linking framework for 1,000 fine-grained entity types and 300 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able to identify entity name mentions, assign a fine-grained type to each mention, and link it to an English KB if it is linkable. Traditional entity linking methods rely on costly human-annotated data to train supervised learning-to-rank models to select the best candidate entity for each mention. In contrast, we propose a novel unsupervised represent-and-compare approach that can accurately capture the semantic meaning representation of each mention, and directly compare its representation with the representation of each candidate entity in the target KB. First, we leverage a deep symbolic semantic representation of the Abstract Meaning Representation to represent contextual properties of mentions. Then we enrich the representation of each contextual word and entity mention with a novel distributed semantic representation based on cross-lingual joint entity and word embedding. We develop a novel method to generate cross-lingual data that is a mix of entities and contextual words based on Wikipedia. This distributed semantics enables effective entity extraction and linking. Because the joint entity and word embedding space is constructed across languages, we further extend it to all 300 Wikipedia languages and fine-grained entity extraction and linking for 1,000 entity types defined in YAGO. Finally, using knowledge-driven question answering as a case study, we demonstrate the effectiveness of acquiring external knowledge using entity extraction and linking to improve downstream applications. Keyword: cross-lingual; entity extraction; entity linking URL: http://hdl.handle.net/2142/109431 BASE Hide details 10 Multi-Source Attention for Unsupervised Domain Adaptation. Bollegala, Danushka; Cui, Xia. - : Association for Computational Linguistics, 2020 BASE Show details 11 Neighbors helping the poor: improving low-resource machine translation using related languages [<Journal>] Pourdamghani, Nima [Verfasser]; Knight, Kevin [Verfasser] DNB Subject Category Language Show details 12 Learning from Past Mistakes: Improving Automatic Speech Recognition Output via Noisy-Clean Phrase Context Modeling ... Shivakumar, Prashanth Gurunath; Li, Haoqi; Knight, Kevin. - : arXiv, 2018 BASE Show details 13 Multi-lingual Common Semantic Space Construction via Cluster-consistent Word Embedding ... Huang, Lifu; Cho, Kyunghyun; Zhang, Boliang. - : arXiv, 2018 BASE Show details 14 Abstract Meaning Representation (AMR) Annotation Release 2.0 Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017 BASE Show details 15 Abstract Meaning Representation (AMR) Annotation Release 2.0 ... Knight, Kevin; Badarau, Bianca; Baranescu, Laura. - : Linguistic Data Consortium, 2017 BASE Show details 16 Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features Wiegand, Michael [Verfasser]; Schulder, Marc [Verfasser]; Ruppenhofer, Josef [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2016 DNB Subject Category Language Show details 17 Opinion Holder and Target Extraction on Opinion Compounds – A Linguistic Approach Wiegand, Michael [Verfasser]; Bocionek, Christine [Verfasser]; Ruppenhofer, Josef [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2016 DNB Subject Category Language Show details 18 Leadership discourse as basis and means for developing L2 students into future leaders Knight, Kevin; Candlin, Chris. - : Reading, UK : Garnet Publishing, 2015 BASE Show details 19 Analysing the discourses of leadership as a basis for developing leadership communication skills in a second or foreign language Knight, Kevin. - : Sydney, Australia : Macquarie University, 2015 BASE Show details 20 Statistical Techniques for Translating to Morphologically Rich Languages (Dagstuhl Seminar 14061) Koehn, Philipp; Uszkoreit, Hans; Schmid, Helmut. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2014. : Dagstuhl Reports. Dagstuhl Reports, Volume 4, Issue 2, 2014 BASE Show details Page: 1 2 3

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