Relevant bibliographies by topics / Translation by DEEPL

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Translation by DEEPL'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Translation by DEEPL"

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Dora Nurcahyani, Feby, Dimas Adika, and Widyasari. "Translating the Untranslatable: DeepL and ChatGPT on Academic Idioms." Linguistik Terjemahan Sastra (LINGTERSA) 5, no. 2 (2024): 85–93. http://dx.doi.org/10.32734/lingtersa.v5i2.15086.

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This research explores the efficacy of two prominent machine translation platforms, DeepL and ChatGPT, in translating academic idioms from English to Indonesian. Academic idioms, situated between discipline-specific jargon and universally understood expressions, pose a challenge for existing translation systems, particularly those rooted in Neural Machine Translation (NMT). The study employs a qualitative descriptive methodology, focusing on translation precision and naturalness, with bilingual experts evaluating translations through a questionnaire, focusing on translation precision and natur
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Telaumbanua, Yasminar Amaerita, Angelin Marpaung, Ceria Putri Damai Gulo, Dodi Kardo Wijaya Waruwu, Erika Zalukhu, and Novita Purnawirati Zai. "Analysis of Two Translation Applications : Why is DeepL Translate more accurate than Google Translate?" Journal of Artificial Intelligence and Engineering Applications (JAIEA) 4, no. 1 (2024): 82–86. http://dx.doi.org/10.59934/jaiea.v4i1.560.

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DeepL Translate and Google Translate are two leading machine translation tools. The focus of this research is to analyze the accuracy of translation results provided by DeepL Translation and Google Translation specifically in translating English to Indonesian. This research used a qualitative approach of document analysis and interviews. The advanced neural machine translation technology of DeepL, by utilizing extensive data, enables it to recognize language nuances and provide contextually accurate translations. In contrast, Google Translate, despite having grown to be supported by hundreds o
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Karabayeva, Irina, and Anna Kalizhanova. "Evaluating machine translation of literature through rhetorical analysis." Journal of Translation and Language Studies 5, no. 1 (2024): 1–9. http://dx.doi.org/10.48185/jtls.v5i1.962.

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This paper looks at how well ChatGPT and DeepL, two AI tools, translate literary works. Not only can ChatGPT translate text, but it can also carry out other jobs. DeepL is a service that performs computer translation and uses neural networks. The paper looks at how ChatGPT and DeepL translate books, poems, and dialogues compared to translations done by humans. The paper also talks about the pros and cons of using machine translation for literary reasons, including issues of creativity, style, and adapting to different cultures. The paper uses both new and old studies on machine translation tec
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Uryadi, Uryadi, Rina Agustin, and Azka Adilya Rachma. "Translation of Kompositum of German Legal Texts Into Indonesian: A Comparative Analysis Between Google Translate And DeepL." Interference: Journal of Language, Literature, and Linguistics 6, no. 1 (2025): 11. https://doi.org/10.26858/interference.v6i1.70473.

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Abstract. This study examines the translation of kompositum (compound words) in German legal texts into Indonesian through a qualitative comparative analysis of two machine translation tools: Google Translate and DeepL. The analysis is conducted based on three key criteria: accuracy, acceptability, and readability. Selected legal texts containing complex kompositum, such as "ärztliche Bescheinigung für Jugendliche” and “Berufsausbildungsvertrag”, are analyzed to evaluate the performance of each tool in conveying meaning, contextual appropriateness, and linguistic fluency. The findings reveal t
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Sabrina, Sabrina, Mina Fadhillah, Flora Oktaviani Chawdri, Cut Safara, and Lara Juniarti. "Contrastive Analysis of DeepL Translation vs. Google Translate’s Performance in Rendering Academic Texts: Insights from EFL Learners." Jurnal Serambi Ilmu 26, no. 1 (2025): 73–82. https://doi.org/10.32672/jsi.v26i1.2502.

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Numerous online translation tools are available today to assist academic works. This study aimed to explore English students’ insights regarding two most popular translation tools, namely DeepL Translation and Google Translate in terms of accuracy, naturalness, grammar, context understanding, terminology translation, speed, language pairs, and additional features of both tools. This research is descriptive qualitative. Thirty English students of Universitas Serambi Mekkah filled in a Likert-scale questionnaire comprising 10 items. Their responses were analyzed using Thematic Analysis. The find
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Stepanov, Ievgenii M., та Zhongzheng Wang. "STRATEGIES FOR TRANSLATING CULTURALLY LOADED INFORMATION FROM CHINESE IN THE CONTEXT OF THE USE OF ARTIFICIAL INTELLIGENCE (BASED ON THE TRANSLATION OF YU HUA’S NOVEL “TO LIVE” / “活着»)". Мова, № 42 (19 листопада 2024): 21–28. https://doi.org/10.18524/2307-4558.2024.42.325845.

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The purpose of this study is a comparative analysis of the use of machine and human translation of the text of fiction. The object of the analysis is the translation of culturally loaded information from the novel “活着» / «To Live» by the modern Chinese writer Yu Hua (余华) into Russian. The human translation of Roman Shapiro and online machine translations of the ChatGPT chatbot based on a neural network developed by OpenAI, and of the DeepL (DeepL GmbH) were compared. The subject of the study is the optimal possibilities of combining modern translation strategies with the involvement of human a
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Hasanah, Ummi, Lulu Eka Aprilia, Muhammad Fahmi, Rifki Maulana Hidayat, and Aulia Fadhila Wirmansyah. "Akurasi Hasil Terjemahan Puisi Nizar Qabbani “Asyhadu An La Imraatan Illa Anti” Menggunakan Deepl Translator." Deskripsi Bahasa 8, no. 1 (2025): 39–56. https://doi.org/10.22146/db.13977.

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The rapid advancement of machine translation today is influenced by the progress in human intelligence. For instance, DeepL, as a translation machine, is considered highly accurate. The aim of this research was to analyze the accuracy of the translation of Nizar Qabbani's poem “Asyhadu An La Imra’atan Illa Anti” using Nababan's and Paul Ricoeur's theories. This study is qualitative in nature and employs a reading and note-taking method. Data analysis techniques followed Miles and Huberman's methods. Based on the research results, conclusions were drawn according to the research questions. Out
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Olkhovska, Alla, and Liliya Levchenko. "Experimental study of the impact of using hybride machine translation engines on the quality of translation of texts in the field of ornamental horticulture." 98, no. 98 (December 25, 2023): 48–52. http://dx.doi.org/10.26565/2786-5312-2023-98-06.

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The article is devoted to the study of the impact of using hybrid machine translation engines (Onlinedoctranslator and DeepL Translate) on the quality of translation of texts in the field of ornamental horticulture. Within our experimental study the quality of translation was determined by the number of errors and quality of rendering horticultural terminology. Machine translation is gradually evolving, the market is extremely active and proposes many new engines uniting most promising algorithms, but it is important to determine the effectiveness of hybrid machine translation engines in trans
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Asmara, Devi Sunita Mutia, and Farida Repelitawati Br Kembaren. "Student’s Perception Towards the Use of DeepL Translator in Writing Thesis or Journal for English Education Students." IJLECR - INTERNATIONAL JOURNAL OF LANGUAGE EDUCATION AND CULTURE REVIEW 10, no. 1 (2024): 117–26. http://dx.doi.org/10.21009/ijlecr.v10i1.47937.

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Translation is a crucial aspect for non-native English students, especially when writing academic theses or journals. This study aims to discuss the use of the DeepL Translator application in writing a thesis or journal of English students. This research employs qualitative methods with a case analysis design by analyzing data derived from questionnaire data and deeper interviews related to the use of DeepL Translator. The use of questionnaire data and further interviews were conducted with 24 final semester English students. The data were analyzed using Miles and Huberman's techniques, which
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Sun, Rui. "Evaluating the Translation Accuracy of ChatGPT and DeepL Through the Lens of Implied Subjects." Arab World English Journal For Translation and Literary Studies 8, no. 4 (2024): 41–53. http://dx.doi.org/10.24093/awejtls/vol8no4.5.

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This research aims to offer deeper insights into the translation quality of large language models and neural machine translation systems. It compares the performance of two state-of-the-art models, ChatGPT and DeepL, to explore which system achieves higher translation accuracy. This research employs a highly focused and specialized method to evaluate translation performance, enabling the identification of nuanced differences between advanced AI/machine models. It focuses on implied subjects in contemporary Chinese writer Qiuyu Yu’s Iraq travelogue and examines how the two models handle these i
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Dissertations / Theses on the topic "Translation by DEEPL"

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Marcassoli, Giulia. "Gli output dei sistemi di traduzione automatica neurale: valutazione della qualità di Google Translate e DeepL Translator nella combinazione tedesco-italiano." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19536/.

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MT is becoming a powerful tool for professional translators, language service providers and common users. The present work focuses on its quality, evaluating the translations produced by two neural MT systems – i.e. Google Translate and DeepL Translator – through manual error annotation. The data set used for this task is composed of semi-specialized German texts translated into Italian. Aim of the present work is to assess the quality of MT outputs for the data set considered and obtain a detailed overview of the type of errors made by the two neural MT systems examined. The first part of thi
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Luccioli, Alessandra. "Stereotipi di genere e traduzione automatica dall'inglese all’italiano: uno studio di caso sul femminile nelle professioni." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20408/.

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La presente tesi si pone come obiettivo quello di indagare il rapporto tra stereotipi di genere e traduzione automatica, proponendo uno studio di caso composto da frasi contenenti dei sostantivi riferiti a professioni tradotti automaticamente dall’inglese all’italiano. Il capitolo I offre una panoramica teorica sulla traduzione automatica, per poi approfondire il tema degli stereotipi di genere nella traduzione automatica. Il capitolo II si concentra invece sul rapporto tra genere e lingua, partendo dalla definizione di stereotipi e pregiudizi per passare poi alla questione dei femminili profe
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Braghittoni, Laura. "La localizzazione software: proposta di traduzione della documentazione di memoQ." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20421/.

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ABSTRACT The modern world is becoming every day more and more tied to technology. The technological development of the last thirty years has led us to live in a digital world dominated by the Internet, which today reaches more than 4 billion users worldwide. Thus computers, smartphones and tablets are now part of everyday life for more and more people. Behind the worldwide spread of modern technologies we find localization, which plays a key role in our society, despite being barely known by non-experts. Every day localization enables users all around the world to access digital products and
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Di, Gangi Mattia Antonino. "Neural Speech Translation: From Neural Machine Translation to Direct Speech Translation." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/259137.

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Sequence-to-sequence learning led to significant improvements to machine translation (MT) and automatic speech recognition (ASR) systems. These advancements were first reflected in spoken language translation (SLT) when using a cascade of (at least) ASR and MT with the new "neural" models, then by using sequence-to-sequence learning to directly translate the input audio speech into text in the target language. In this thesis we cover both approaches to the SLT task. First, we show the limits of NMT in terms of robustness to input errors when compared to the previous phrase-based state of the
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Di, Gangi Mattia Antonino. "Neural Speech Translation: From Neural Machine Translation to Direct Speech Translation." Doctoral thesis, Università degli studi di Trento, 2020. http://hdl.handle.net/11572/259137.

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Sequence-to-sequence learning led to significant improvements to machine translation (MT) and automatic speech recognition (ASR) systems. These advancements were first reflected in spoken language translation (SLT) when using a cascade of (at least) ASR and MT with the new "neural" models, then by using sequence-to-sequence learning to directly translate the input audio speech into text in the target language. In this thesis we cover both approaches to the SLT task. First, we show the limits of NMT in terms of robustness to input errors when compared to the previous phrase-based state of the
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Kan, Jichao. "Visual-Text Translation with Deep Graph Neural Networks." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23759.

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Visual-text translation is to produce textual descriptions in natural languages from images and videos. In this thesis, we investigate two topics in the field: image captioning and continuous sign language recognition, by exploring structural representations of visual content. Image captioning is to generate text descriptions for a given image. Deep learning based methods have achieved impressive performance on this topic. However, the relations among objects in an image have not been fully explored. Thus, a topic-guided local-global graph neural network is proposed to extract graph propertie
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Olmucci, Poddubnyy Oleksandr. "Investigating Single Translation Function CycleGANs." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/16126/.

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With the advent of Deep Learning, we have been able to find solutions to many problems which didn't have an algorithmic solution, among these the image-to-image translation problem. One approach to solve it is by using the CycleGAN framework, which allows to learn mappings between two given image categories (or classes) that aren't necessarily paired. In this dissertation we present some attempts that were done in order to use the CycleGAN approach to perform image translations between more than two image classes at a time.
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Janakiraman, Laxmipreethi. "Deep Directive Attention Network(DDAN) based Sign Language Translation." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/26581.

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Sign language is a visual language. It is an effective way of communication for hearing and speech impaired community. In general, all visual languages are multi-modal which utilizes hand gestures, facial expressions and other non-manual features to effectively consider the linguistics of the language while communicating with others. In the recent few years, due to the advancement of computer vision and the NLP field, Sign Language Recognition(SLR) and Sign Language Translation(SLT) topic has attracted many researchers to find an effective way to translate sign language videos to spoken langua
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Caglayan, Ozan. "Multimodal Machine Translation." Thesis, Le Mans, 2019. http://www.theses.fr/2019LEMA1016/document.

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La traduction automatique vise à traduire des documents d’une langue à une autre sans l’intervention humaine. Avec l’apparition des réseaux de neurones profonds (DNN), la traduction automatique neuronale(NMT) a commencé à dominer le domaine, atteignant l’état de l’art pour de nombreuses langues. NMT a également ravivé l’intérêt pour la traduction basée sur l’interlangue grâce à la manière dont elle place la tâche dans un cadre encodeur-décodeur en passant par des représentations latentes. Combiné avec la flexibilité architecturale des DNN, ce cadre a aussi ouvert une piste de recherche sur la
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Chatterjee, Rajen. "Automatic Post-Editing for Machine Translation." Doctoral thesis, Università degli studi di Trento, 2019. http://hdl.handle.net/11572/242495.

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Automatic Post-Editing (APE) aims to correct systematic errors in a machine translated text. This is primarily useful when the machine translation (MT) system is not accessible for improvement, leaving APE as a viable option to improve translation quality as a downstream task - which is the focus of this thesis. This field has received less attention compared to MT due to several reasons, which include: the limited availability of data to perform a sound research, contrasting views reported by different researchers about the effectiveness of APE, and limited attention from the industry to use
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Books on the topic "Translation by DEEPL"

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Cooper, Arthur R. V., d. 1988., ed. The Deep woods' business: Uncollected translations from the Chinese. Wellsweep, 1990.

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Marieluise, Fleisser. Marieluise Fleisser's 'The deep sea fish': A translation and critical examination. University Microfilms, 1997.

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Haroutyunian, Sona, and Dario Miccoli. Orienti migranti: tra letteratura e traduzione. Fondazione Università Ca’ Foscari, 2020. http://dx.doi.org/10.30687/978-88-6969-499-8.

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The book series, edited by Nicoletta Pesaro and sponsored by the Department of Asian and North African Studies, aims to give voice to a time-honoured branch of theoretical and practical research across the disciplines and research domains within the Department. The series aims to establish a platform for scholarly discussion and a space for international dialogue on the translation of Asian and North African languages. In doing so, the project aims to observe and verify the translingual and transcultural dynamics triggered by translation from and into said ‘languages-cultures’, as well as to i
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L, Blanc P., and Atomic Energy of Canada Limited., eds. An AECL research translation of a CEA report the new OKLO reaction zones (Gabon): Report onmission (July 1988) and study project on the long-term migration processes of elements within a deep geochemical system. AECL, Whiteshell Nuclear Research Establishment, 1992.

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Tolkien, J. R. R. Die Koning Keer Terug: Die derde deel van DIE HEERSER VAN DIE RINGE. Protea Boekhuis, 2020.

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Favaro, Alice. Después de la caída del ‘ángel’. Edizioni Ca' Foscari, 2020. http://dx.doi.org/10.30687/978-88-6969-416-5.

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Ángel Bonomini was born in Buenos Aires in 1929 where he lived until his death at the age of sixty-four in 1994. He worked for various newspapers and magazines as an art critic and translator, but always maintaining his literary activity. He inherited the tradition of the Argentine fantastic and was a prolific writer: his production includes essays, poems and fantastic tales.Although he lived in a period of great cultural splendor and his literary talent was recognised by authors such as Borges and Bioy Casares, he fell into an unexplained oblivion, disappearing quite early from the contempora
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Machine Translation. MIT Press, 2017.

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Machine Translation. MIT Press, 2017.

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Eigler, Ulrich. Between Voß and Schröder. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198810810.003.0025.

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This chapter argues that German translations of Virgil are the result of a complicated process, in which history of reception and history of translations move alongside one another. It explores the interaction between translations of Virgil and translations of Homer, giving particular attention to the role of the authoritative translation of Homer by Johann Heinrich Voß. It demonstrates that the discourse on translations of Virgil since the eighteenth century is deeply entwined with literary, aesthetic, and political questions, which are closely entangled with the German struggle for unity and
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Merril, Adrienne. Deep Yogic Breathing : Pranayama Definition: Pranayama Translation. Independently Published, 2021.

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Book chapters on the topic "Translation by DEEPL"

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Speranza, Giulia, and Johanna Monti. "Chapter 3. Evaluating the Italian-English machine translation quality of MWUs in the domain of archaeology." In Current Issues in Linguistic Theory. John Benjamins Publishing Company, 2024. http://dx.doi.org/10.1075/cilt.366.03spe.

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Multiword units (MWUs) represent a challenging and problematic linguistic issue in the field of Natural Language Processing (NLP) due to their idiosyncratic nature. This paper investigates the quality of Neural Machine Translation (NMT) outputs when dealing with MWUs in the domain of archaeology. As a case study, a dataset of 100 MWUs is used as a Gold Standard to evaluate out-of-context and in-context translation outputs from three state-of-the-art NMT systems for the Italian-English language pair: Google Translate, DeepL, and Microsoft Bing Translator. MT outputs are manually evaluated with
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Li, Linlin. "Translation Project Terminology Management Based on Artificial Intelligence Translator DeepL." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-7999-7_34.

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Colson, Jean-Pierre. "Chapter 1. Multi-word units in neural machine translation." In Current Issues in Linguistic Theory. John Benjamins Publishing Company, 2024. http://dx.doi.org/10.1075/cilt.366.01col.

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Neural machine translation (NMT) has recently made significant progress in improving the quality of the texts it produces. New features of NMT include the fluidity of translations and the successful handling of multi-word units. In this paper we first report the results of an automated evaluation of the percentage of phraseology in the translations produced by Google Translate and DeepL. A corpus-based approach makes it possible to estimate that both NMT systems succeed in producing an average percentage of phraseology that is quite reasonable and sometimes even higher than in natural language
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Hidalgo-Ternero, Carlos Manuel, and Gloria Corpas Pastor. "Chapter 2. ReGap." In Current Issues in Linguistic Theory. John Benjamins Publishing Company, 2024. http://dx.doi.org/10.1075/cilt.366.02hid.

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This research presents ReGap, a text-preprocessing algorithm for the automatic token-based identification and conversion of discontinuous multiword expressions (MWEs) into their canonical state, i.e., their continuous form, as a means to optimise neural machine translation (NMT) systems. To this end, an experiment with flexible verb-noun idiomatic constructions (VNICs) is conducted in order to assess to what extent ReGap can enhance the performance of the most robust NMT system to date, DeepL, under the challenge of MWE discontinuity in the Spanish-into-English and the Spanish-into-German dire
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Skadiņa, Inguna, Andrejs Vasiḷjevs, Mārcis Pinnis, et al. "Deep Dive Machine Translation." In European Language Equality. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28819-7_40.

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AbstractMachine Translation (MT) is one of the oldest language technologies having been researched for more than 70 years. However, it is only during the last decade that it has been widely accepted by the general public, to the point where in many cases it has become an indispensable tool for the global community, supporting communication between nations and lowering language barriers. Still, there remain major gaps in the technology that need addressing before it can be successfully a0146pplied in under-resourced settings, can understand context and use world knowledge. This chapter provides
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Steiner, Riccardo. "“The Deep Open Sea”1 “l’alto mare aperto”." In Translation / Transformation. Routledge, 2021. http://dx.doi.org/10.4324/9781003096399-5.

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Sánchez, Alba Montes. "Medicine, wine, terminology and translation (German-Spanish)." In Text and Wine. John Benjamins Publishing Company, 2023. http://dx.doi.org/10.1075/ivitra.38.10san.

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This paper aims to study the terminology of the wine language in the context of traditional medicine from a translational perspective. The treatment of medical terminology, as well as its translation into Spanish, involves exceptional difficulty due to the level of specialization of this field. In doing so, the professional specialised in medical translation works with a highly specialized language, composed of broad-ranging set of technical terms. Subjected constantly to scientific updating, these terms are conditioned by the influence of other languages, as their long-lived Greco-Latin roots
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Trullo, Roger, Quoc-Anh Bui, Qi Tang, and Reza Olfati-Saber. "Image Translation Based Nuclei Segmentation for Immunohistochemistry Images." In Deep Generative Models. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-18576-2_9.

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Katzir, Oren, Dani Lischinski, and Daniel Cohen-Or. "Cross-Domain Cascaded Deep Translation." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58536-5_40.

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Liu, Yang, and Jiajun Zhang. "Deep Learning in Machine Translation." In Deep Learning in Natural Language Processing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5209-5_6.

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Conference papers on the topic "Translation by DEEPL"

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Wang, Fengjuan. "Methods for Evaluating the Translation Quality of Artificial Intelligence Translator DEEPL Based on Multi Translation Parallel Corpus." In 2024 First International Conference on Software, Systems and Information Technology (SSITCON). IEEE, 2024. https://doi.org/10.1109/ssitcon62437.2024.10796803.

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Chen, Mengkun, Sanidhya D. Tripathi, and James W. Tunnell. "Raman Spectrum Denoising Using Deep Learning." In Clinical and Translational Biophotonics. Optica Publishing Group, 2025. https://doi.org/10.1364/translational.2025.tm1f.3.

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We developed a deep learning-based method to denoise low-SNR Raman signals from skin by learning sample-independent instrument noise. This approach enhances spectral recovery, improves SNR by around 33dB, and enables accurate component concentration analysis.
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Kifle, Naomi, Bo Ning, Saige Teti, et al. "Intraoperative Detection and Segmentation of Pediatric Epilepsy-Related Brain Abnormalities Using a Deep Learning Model." In Clinical and Translational Biophotonics. Optica Publishing Group, 2025. https://doi.org/10.1364/translational.2025.tw2f.4.

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We present a deep learning-based classification and segmentation model that can identify epileptogenic tissue intraoperatively from pediatric patients diagnosed with epilepsy undergoing neurosurgical resection.
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Liu, Chenglin, and Yutong Wen. "Research on Information Distortion Control in Real-Time News Translation Based on Machine Translation and Semantic Similarity Evaluation." In 2025 6th International Conference on Computer Vision, Image and Deep Learning (CVIDL). IEEE, 2025. https://doi.org/10.1109/cvidl65390.2025.11085825.

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Ozcan, Aydogan. "Virtual Staining of Label-Free Tissue Using Deep Learning." In Clinical and Translational Biophotonics. Optica Publishing Group, 2024. https://doi.org/10.1364/translational.2024.ttu3b.1.

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We will report deep learning-based virtual staining techniques to generate various histological stains, including immunohistochemical (IHC) stains, from label-free microscopic images of tissue samples by using autofluorescence microscopy, quantitative phase imaging (QPI) and reflectance confocal microscopy. Full-text article not available; see video presentation
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Balipa, Mamatha, Anwaya K, Ananya, and M. Murugappan. "A Rule-Based Machine Translation Framework for Low-Resource Language Pairs." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE, 2025. https://doi.org/10.1109/icsadl65848.2025.10933067.

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Wang, Bing. "Construction of English Chinese translation units and translation models based on deep learning algorithms." In 2024 3rd International Conference for Advancement in Technology (ICONAT). IEEE, 2024. https://doi.org/10.1109/iconat61936.2024.10774857.

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ILIE, ALEXANDRA. "Traducerea automată a literaturii. O himeră încă vie?" In Interdisciplinary Perspectives in Humanities and Social Sciences: “Rethinking Values in Interdisciplinary Research”. EDITURA UNIVERSITĂȚII „ALEXANDRU IOAN CUZA” DIN IAŞI, 2024. https://doi.org/10.47743/phss-2024-0004.

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Artificial intelligence is about to reshape the world and redefine the relationship humans maintain with their professional activities. Recent machine translation systems, as well as the prior generation of statistical machine translation, rely on extensive aligned corpora and generate outputs whose quality can compete with human translations. This is particularly the case for technical and even medical texts. The role of the translator is to be questioned. Could algorithms potentially substitute this profession? Certain texts types, such as legal and literary ones, remain resistant to machine
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Bao, Yue, and Yi Zhang. "Quality Assessment of Machine Translation from Translation Criticism Perspective—A Case Study of Chinese Translation of a Speech by Neural Machine Translator DeepL." In 2023 3rd International Conference on Educational Technology (ICET). IEEE, 2023. http://dx.doi.org/10.1109/icet59358.2023.10424111.

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Rescigno, Argentina Anna, and Johanna Monti. "Gender Bias in Machine Translation: a statistical evaluation of Google Translate and DeepL for English, Italian and German." In International Conference on Human-informed Translation and Interpreting Technology 2023. INCOMA Ltd., Shoumen, Bulgaria, 2023. http://dx.doi.org/10.26615/issn.2683-0078.2023_001.

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Reports on the topic "Translation by DEEPL"

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Tellei, Adeeshia, King Sam, Megan Cook, et al. Omesubel a Nautilus - Ocean Exploration Vocabulary in Palauan Language. Ocean Exploration Trust, 2024. http://dx.doi.org/10.62878/bgj821.

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This learning resource includes a glossary of ocean exploration and technology terms in Palauan language along with their definitions and translations into English. It was developed in support of Lebuu’s Voyage I & II — the 2024 deep ocean exploration expeditions aboard E/V Nauutilus led by Ocean Exploration Trust, Palau International Coral Reef Center, and NOAA Ocean Exploration in the Palau National Marine Sanctuary. Its contents are certified by the Palau Language Commission. The Lebuu’s Voyage expeditions were funded by NOAA Ocean Exploration via the Ocean Exploration Cooperative Insti
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Mehta, Goverdhan, Alain Krief, Henning Hopf, and Stephen A. Matlin. Chemistry in a post-Covid-19 world. AsiaChem Magazine, 2020. http://dx.doi.org/10.51167/acm00013.

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The long-term impacts of global upheaval unleashed by Covid-19 on economic, political, social configurations, trade, everyday life in general, and broader planetary sustainability issues are still unfolding and a full assessment will take some time. However, in the short term, the disruptive effects of the pandemic on health, education, and behaviors and on science and education have already manifested themselves profoundly – and the chemistry arena is also deeply affected. There will be ramifications for many facets of chemistry’s ambit, including how it repositions itself and how it is taugh
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Pikilnyak, Andrey V., Nadia M. Stetsenko, Volodymyr P. Stetsenko, Tetiana V. Bondarenko, and Halyna V. Tkachuk. Comparative analysis of online dictionaries in the context of the digital transformation of education. [б. в.], 2021. http://dx.doi.org/10.31812/123456789/4431.

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The article is devoted to a comparative analysis of popular online dictionaries and an overview of the main tools of these resources to study a language. The use of dictionaries in learning a foreign language is an important step to understanding the language. The effectiveness of this process increases with the use of online dictionaries, which have a lot of tools for improving the educational process. Based on the Alexa Internet resource it was found the most popular online dictionaries: Cambridge Dictionary, Wordreference, Merriam–Webster, Wiktionary, TheFreeDictionary, Dictionary.com, Glos
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Carter, Hilary, and Jessica Groopman. Diversity, Equity, and Inclusion in Open Source: Exploring the Challenges and Opportunities to Create Equity and Agency Across Open Source Ecosystems. The Linux Foundation, 2021. https://doi.org/10.70828/kewr6778.

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Diversity, equity, and inclusion (DEI) in the technology industry — and within open source specifically—is an opportunity we need to continuously leverage for the benefits it brings. Given that people of vastly different backgrounds, nationalities, orientations, and identities create open source software, hardware, and standards, their participation and well-being is important. Study after study reveals that diversity in participation produces better outcomes and more robust technologies—that diverse communities are simply stronger communities. For communities to continue evolving for the bett
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