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DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues
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In: Castilho, Sheila orcid:0000-0002-8416-6555 , Cavalheiro Camargo, João Lucas orcid:0000-0003-3746-1225 , Menezes, Miguel and Way, Andy orcid:0000-0001-5736-5930 (2021) DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues. In: Sixth Conference on Machine Translation (WMT21), 10-11 Nov 2021, Punta Cana, Dominican Republic (Online). ISBN 978-1-954085-94-7 (2021)
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Large-scale study of speech acts' development using automatic labelling
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In: Proceedings of the 43rd Annual Meeting of the Cognitive Science Society ; https://hal.archives-ouvertes.fr/hal-03234620 ; Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, Jul 2021, Vienna, Austria (2021)
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Multitask Transformer Model-based Fintech Customer Service Chatbot NLU System with DECO-LGG SSP-based Data ; DECO-LGG 반자동 증강 학습데이터 활용 멀티태스크 트랜스포머 모델 기반 핀테크 CS 챗봇 NLU 시스템
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In: Annual Conference on Human and Language Technology ; https://hal.archives-ouvertes.fr/hal-03603903 ; Annual Conference on Human and Language Technology, Oct 2021, Séoul, South Korea. pp.461-466 ; http://www.koreascience.or.kr/journal/OOGHAK.page (2021)
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Automatic Language Identification in Code-Switched Hindi-English Social Media Text
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In: Journal of Open Humanities Data; Vol 7 (2021); 7 ; 2059-481X (2021)
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Semi-automatic Annotation Proposal for Increasing a Fake News Dataset in Spanish
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POS-Tagging für Transkripte gesprochener Sprache : Entwicklung einer automatisierten Wortarten-Annotation am Beispiel des Forschungs- und Lehrkorpus Gesprochenes Deutsch (FOLK)
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BLLDB
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UB Frankfurt Linguistik
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SMAD: A tool for automatically annotating the smile intensity along a video record
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In: HRC2020, 10th Humour Research Conference ; https://hal.archives-ouvertes.fr/hal-02529371 ; HRC2020, 10th Humour Research Conference, Mar 2020, Commerce, Texas, United States (2020)
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Automatic annotation of error types for grammatical error correction ...
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PE2 rr corpus: manual error annotation of automatically pre-annotated MT post-edits
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Abstract:
We present a freely available corpus containing source language texts from different domains along with their automatically generated translations into several distinct morphologically rich languages, their post-edited versions, and error annotations of the performed post-edit operations. We believe that the corpus will be useful for many different applications. The main advantage of the approach used for creation of the corpus is the fusion of post-editing and error classification tasks, which have usually been seen as two independent tasks, although naturally they are not. We also show benefits of coupling automatic and manual error classification which facilitates the complex manual error annotation task as well as the development of automatic error classification tools. In addition, the approach facilitates annotation of language pair related issues. ; This publication has emanated from research supported by TRAMOOC project (Translation for Massive Open Online Courses) partially funded by the European Commission under H2020-ICT-2014/H2020-ICT-2014-1 under grant agreement number 644333 and by the Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight). ; non-peer-reviewed
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Keyword:
Error annotation; Machine translation; MT post-edits; PE2rr corpus; Post-editing; Pre-annotated
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URL: http://hdl.handle.net/10379/14894
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| 19 |
Automatic annotation of error types for grammatical error correction
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Annotation des proéminences pour la segmentation de corpus oraux : l’expérience du projet SegCor
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In: CMLF 2018 - 6e Congrès Mondial de Linguistique Française ; https://halshs.archives-ouvertes.fr/halshs-01839314 ; CMLF 2018 - 6e Congrès Mondial de Linguistique Française, Franck Neveu; Bernard Harmegnies; Linda Hriba; Sophie Prévost, Jul 2018, Mons, Belgique (2018)
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