( en | de | ru )

 

Disambiguation

From post

копироватьудалитьдобавить публикацию в буфер
Getting Gender Right in Neural MT.

, , и . EMNLP, стр. 3003-3008. Association for Computational Linguistics, (2018)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

Rafael Isaac Millstein Evan

Franziska-Sophie Evans-von Krbek

Helga Evans

Sotirios Evangelou

Ioannis Evangelou

 

Другие публикации лиц с тем же именем

Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation., , и . MTSummit (1), стр. 222-232. European Association for Machine Translation, (2019)On the Integration of LinguisticFeatures into Statistical and Neural Machine Translation.. CoRR, (2020)A Case Study of Natural Gender Phenomena in Translation. A Comparison of Google Translate, Bing Microsoft Translator and DeepL for English to Italian, French and Spanish., , , и . CLiC-it, том 2769 из CEUR Workshop Proceedings, CEUR-WS.org, (2020)NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender Neutral Alternatives., , и . EMNLP (1), стр. 8940-8948. Association for Computational Linguistics, (2021)ABI Neural Ensemble Model for Gender Prediction., , , , и . GxG@CLIN, том 2453 из CEUR Workshop Proceedings, стр. 53-61. CEUR-WS.org, (2019)Getting Gender Right in Neural MT., , и . EMNLP, стр. 3003-3008. Association for Computational Linguistics, (2018)SuperNMT: Neural Machine Translation with Semantic Supersenses and Syntactic Supertags., и . ACL (3), стр. 67-73. Association for Computational Linguistics, (2018)Prediction of Emotions from Text using Sentiment Analysis for Expressive Speech Synthesis., , и . SSW, стр. 21-26. ISCA, (2016)Tailoring Domain Adaptation for Machine Translation Quality Estimation., , , , , , и . EAMT, стр. 9-20. European Association for Machine Translation, (2023)Europarl Datasets with Demographic Speaker Information., и . EAMT, (2018)