Relevant bibliographies by topics / Google Translate

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  2. Dissertations / Theses
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  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Google Translate'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "Google Translate"

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Fitria, Tira Nur. "ANALYSIS ON CLARITY AND CORRECTNESS OF GOOGLE TRANSLATE IN TRANSLATING AN INDONESIAN ARTICLE INTO ENGLISH." International Journal of Humanity Studies (IJHS) 4, no. 2 (March 31, 2021): 256–66. http://dx.doi.org/10.24071/ijhs.v4i2.3227.

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The objective of this study is to analyze the aspects of clarity and correctness in Google Translate’s ability in translating an Indonesian article from English into Indonesian. This research refers to qualitative research. Data used in this research is a published Indonesian article which is translated into English by using Google Translate. Based on the analysis, the researcher concludes that Google Translate is a machine translator, but there is always going to be potentially less clarity and correctness at the end of the translation product such as in Indonesian articles into English. Because English grammar is a complicated thing to be learned, people perhaps cannot expect more that machine translator understands every aspect of the way human beings communicate with each other. That is why the answer about the clarity and the correctness of Google Translate is that it still has a way to go before it can consistently, clearly, and correctly translate the language without errors. In the clarity aspect, there is still no clarity in English translation by Google Translate, even it translated the language word-for-word. In the correctness aspect, it refers to the mechanical rule in writing which is related to grammar, punctuation, and spelling. Some examples of non-correctness are related to grammar and punctuation errors. Machine translators have come a long way in a short amount of time, but some features still lack good translation such as in aspects of grammar and punctuation.
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Ma'shumah, Nadia Khumairo, Isra F. Sianipar, and Cynthia Yanda Salsabila. "Google Translate Performance in Translating English Passive Voice into Indonesian." PIONEER: Journal of Language and Literature 13, no. 2 (December 31, 2021): 271. http://dx.doi.org/10.36841/pioneer.v13i2.1292.

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A scant number of Google Translate users and researchers continue to be skeptical of the current Google Translate's performance as a machine translation tool. As English passive voice translation often brings problems, especially when translated into Indonesian which rich of affixes, this study works to analyze the way Google Translate (MT) translates English passive voice into Indonesian and to investigate whether Google Translate (MT) can do modulation. The data in this research were in the form of clauses and sentences with passive voice taken from corpus data. It included 497 news articles from the online news platform ‘GlobalVoices,' which were processed with AntConc 3.5.8 software. The data in this research were analyzed quantitatively and qualitatively to achieve broad objectives, depth of understanding, and the corroboration. Meanwhile, the comparative methods were used to analyze both source and target texts. Through the cautious process of collecting and analyzing the data, the results showed that (1) GT (via NMT) was able to translate the English passive voice by distinguishing morphological changes in Indonesian passive voice (2) GT was able to modulate English passive voice into Indonesian base verbs and Indonesian active voice.
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Amilia, Ika Kartika, and Darmawan Eko Yuwono. "A STUDY OF THE TRANSLATION OF GOOGLE TRANSLATE." LINGUA : JURNAL ILMIAH 16, no. 2 (October 31, 2020): 1–21. http://dx.doi.org/10.35962/lingua.v16i2.50.

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ABSTRACT This study is intended to analyze errors made by Google Translate in translating Eliza Riley’s Return to Paradise short story. The method is qualitative descriptive. The data are collected by comparing the translation of Google Translate with that of a professional translator. The errors are analyzed based on Mossop’s revision parameters. The findings show that Google Translate failed to recognize idiomatic expressions which caused fatal errors in the target text; errors in word choice that caused word translated out of context; and illogical sentence at the target text caused by cultural difference. As a conclusion, Google Translate may be useful to help translate few words, phrase, and particular sentence in general, and also gives a general comprehension in translating text. However, it may not give an adequate result as a fine translation product. Keyword: google translate, error analysis, Mossop’s revision parameters
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Winiharti, Menik, Syihabuddin Syihabuddin, and Dadang Sudana. "On Google Translate: Students’ and Lecturers’ Perception of the English Translation of Indonesian Scholarly Articles." Lingua Cultura 15, no. 2 (November 30, 2021): 207–14. http://dx.doi.org/10.21512/lc.v15i2.7335.

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The research investigated the translation results of Google Translate based on the users’ perceptions. It was aimed at describing the users’ frequency in using Google Translate web, finding the users’ perceptions on the acceptability and the readability of Google Translation in translating scholarly articles from Indonesian into English, as well as finding whether students and lecturers have the same perceptions regarding these two criteria. The data were collected from scholarly articles written in Indonesian then translated into English using Google Translate web. Then a survey regarding this translation was distributed to users; they were students and lecturers of Computer Science/Information Technology/Information System. The analysis was conducted with regard to the acceptability and the readability of the translations using a rating scale of translation assessment. The findings suggest that more than half of the participants often use Google Translate Web, which means that the academics are part of the users of Google Translate. However, students and lecturers have a rather different perception of the results of Google Translate. Students consider Google Translate quite acceptable and readable, while lecturers view Google Translate as rather acceptable and moderately readable. In addition, the findings indicate that, to some extent, Google Translate still translates the Indonesian text into English literally.
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Putra, I. Putu Ambara. "The Translation Process of Machine Translation for Cultural Terms on Balinese Folktales." Linguistika: Buletin Ilmiah Program Magister Linguistik Universitas Udayana 29, no. 1 (March 8, 2022): 27. http://dx.doi.org/10.24843/ling.2022.v29.i01.p04.

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The goal of this study is to determine the capability of Google Translate in term of translating cultural terms. This study is conducted to analyze the translation performed by one of the well-known machine translation, Google Translate. The data is collected from the translation of seven traditional Balinese folktales chosen in random via online, namely Manik Angkeran, Kebo Iwa, Lubdaka, Tampaksiring, Origin of Bali, Origin of Singaraja, and Pan Balang Tamak. The data of the study is the translation on cultural terms translated by Google Translate. The cultural terms are classified with Cultural Term Classification Theory by Newmark. The analysis is conducted by comparing the translatied text and the original text to identify the translation method utilized by Google Translate in translating cultural term into English. The Translation Method Theory and Classification by Newmark is used to identify the method of translation utilized by Google Translate. The methods then is used in order to determine the tendency of Google Translate in the translation toward cultural terms.
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Wulansari, Dwi Windah. "Bias Gender Dalam Perbandingan Hasil Terjemahan Buku Cerita Anak Dongeng Bawang Merah Dan Bawang Putih Melalui Penerjemah Dan Google Translate." Wanastra: Jurnal Bahasa dan Sastra 12, no. 2 (September 26, 2020): 229–35. http://dx.doi.org/10.31294/w.v12i2.8516.

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Abstrak - Penelitian ini bertujuan untuk mencari bias gender yang terdapat pada hasil terjemahan buku cerita anak di bandingankan dengan hasil terjemahan google translate. Dalam penelitian ini menggunakan metode deskriptif kualitatif. Sumber data dalam penelitian ini adalah dongeng Bawang Merah dan Bawang Putih yang diterjemahkan dan diceritakan kembali oleh Gibran Maulana dan diterjemahkan melalui aplikasi Google Translate Hasil penerjemahan antara Google Translate dan penerjemah hampir sama yaitu mengenai nama tokoh, nama ganti orang dan nama ganti kepemilikan. Pada aplikasi Google Translate dapat melakukan kesalahan karena konteks, budaya, nama orang, dan kata ganti orang tidak dapat terbaca dalam aplikasi tersebut. sedangakan hasil terjemahan dari penerjemah mengalami human error. Penerjemah dalam buku cerita anak masih belum bisa lepas dari pengaruh ideologi patriarki yang dapat ditujukkan dalam peran gender tradisional yang digambarkan yang membuat peran laki-laki lebih unggul daripada perempuan. Kata Kunci: bias gender, cerita dongeng, google translate Abstract - This study aims to look for gender biases found in the results of the translation of children's storybooks in light with the results of the google translate translation. In this study using a qualitative descriptive method. The data source in this study is the fairy tale of Bawang Merah and Bawang Putih which were translated and retold by Gibran Maulana and translated through the Google Translate application. The results of the translation between Google Translate and the translator are almost the same, namely regarding the names of characters, people's names and ownership names. The Google Translate application can make mistakes because the context, culture, people's names, and pronouns cannot be read in the application. while the translation results from translators experienced human error. Translators in children's story books still cannot be separated from the influence of patriarchal ideology which can be shown in traditional gender roles which are described which make the role of men superior to women. Keyoword : gender bias, fairy tales, google translate
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van Arnhem, Jolanda-Pieta. "Google Translate App." Charleston Advisor 17, no. 3 (January 1, 2016): 24–27. http://dx.doi.org/10.5260/chara.17.3.24.

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Daly, Shelagh. "Google Translate app." Nursing Standard 28, no. 29 (March 19, 2014): 33. http://dx.doi.org/10.7748/ns2014.03.28.29.33.s38.

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Johnson, Gregory. "Google Translate http://translate.google.com/." Technical Services Quarterly 29, no. 2 (March 5, 2012): 165. http://dx.doi.org/10.1080/07317131.2012.650971.

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Fitria, Tira Nur. "Gender Bias in Translation Using Google Translate: Problems and Solution." Language Circle: Journal of Language and Literature 15, no. 2 (April 26, 2021): 285–92. http://dx.doi.org/10.15294/lc.v15i2.28641.

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This study discusses gender bias in terms of language especially from Indonesian into English translation by using Google Translate. This research is descriptive qualitative research. The result shows that most likely every language has gender-biased sides, including English because the type of society in the reality of life is more represented by men and women. In Google translate, the unequal differences between men and women translated into google translate causes the system to be considered biased and sexist towards gender. Whereas in fact, nowadays all genders can have various activities and jobs. Indonesian is also a gender-neutral language. When google translates to change into English, the sentence becomes gendered. The Indonesian language in this case seems to have been saved from being sexist because it does not associate a particular profession or activity with any gender. Unlike English, which adjusts personal pronouns based on gender. Google Translate is not always accurate, especially when translating from English to other languages. That is where Google Translate tends to go astray. The problem is that many languages have gender-based words, whereas English does not. But some words, like profession or occupation, can be masculine or feminine depending on the subject of the sentence, by assigning gender to certain adjectives and words that describe them. Equality in gender and race has been very difficult to achieve in machine technology situations because these systems are trained on existing content, and are not demographically representative. Google decided to make changes. It is important to adapt and build technology that can better serve humans. What may seem like small changes to everyday life are big steps towards gender equality. The way people speak their respective languages is one of the strongest ways of gender discrimination.
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Dissertations / Theses on the topic "Google Translate"

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Repo, Hans. "Hur påverkar Google translate texten? : En studie av hur Google translate som hjälpmedel påverkar textens kvalitet när SVA-elever på nybörjarnivå skriver." Thesis, Luleå tekniska universitet, Institutionen för hälsa, lärande och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85846.

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I studien undersöktes hur elever som undervisas i svenska som andraspråk (SVA) på nybörjar­nivå i grundskolans senare del skrev texter med hjälp av Google translate (GT). Frågeställ­ningen var hur GT som hjälpmedel vid skrivuppgifter påverkade texternas olika kvaliteter jäm­fört med en text skriven utan hjälpmedel. Sju elever deltog i studien. Varje elev skrev två texter var: en med hjälp av GT, och en utan. De båda texterna bedömdes kvalitativt och jämfördes med varandra. Resultatet visade att GT hjälpte eleverna att skapa ett säkrare språk avseende språkets form: till exempel meningsbyggnad, grammatik, stavning och interpunktion. GT hjälpte även elever­na till en mer varierad vokabulär, men denna vokabulär saknade ofta precision vilket skapade begriplighetsproblem. Texterna som skrevs utan GT hade ett mindre varierat ordförråd, men vokabulären var mer anpassad till sitt sammanhang, och därmed höll texterna en högre kom­munikativ och innehållslig kvalitet. GT kunde alltså hjälpa eleverna på nybörjarnivå att uttrycka sig genom att bidra med ett formellt korrekt språk och varierad vokabulär. Men resultaten visade samtidigt att eleverna har allt för liten tilltro till sin egen förmåga, och för stor till GT:s översättningar, vilket skapade texter vars innehåll kunde vara svårt att begripa.
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Josefsson, Elaina. "Contemporary Approaches to Translation in the Classroom : A study of students' Attitudes and Strategies." Thesis, Högskolan Dalarna, Engelska, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:du-5929.

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The purpose of this study is to explore the strategies and attitudes of students towards translation in the context of language learning. The informants come from two different classes at an Upper Secondary vocational program. The study was born from the backdrop of discussions among some English teachers representing different theories on translation and language learning, meeting students endeavoring in language learning beyond the confinement of the classroom and personal experiences of translation in language learning. The curriculum and course plan for English at the vocational program emphasize two things of particular interest to our study; integration of the program outcomes and vocational language into the English course - so called meshed learning – and student awareness of their own learning processes. A background is presented of different contrasting methods in translation and language learning that is relevant to our discussion. However, focus is given to contemporary research on reforms within the Comparative Theory, as expressed in Translation in Language and Teaching (TILT), Contrastive Analysis and “The Third Space”. The results of the students’ reflections are presented as attempts to translate two different texts; one lyric and one technical vocational text. The results show a pragmatic attitude among the students toward tools like dictionaries or Google Translate, but also a critical awareness about their use and limits. They appear to prefer the use of first language to the target language when discussing the correct translation as they sought accuracy over meaning. Translation for them was a natural and problem-solving event worth a rightful place in language teaching.
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Cozza, Antonella. "Google Translate e DeepL: la traduzione automatica in ambito turistico." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Il presente elaborato ha come scopo quello di analizzare il comportamento dei due traduttori automatici più utilizzati attualmente, Google Translate e DeepL, sulla base di testi pertinenti all'ambito turistico, nello specifico, le recensioni di strutture alberghiere. Dopo un breve inquadramento teorico sulla traduzione automatica e sulle principali caratteristiche dei TA sopra citati, si passerà a un esperimento di traduzione dallo spagnolo all'italiano che li coinvolgerà in maniera diretta prendendo in considerazione tre diverse tipologie di recensione. Nel secondo capitolo, verranno valutate le proposte di traduzione offerte da Google Translate e DeepL in base a problemi linguistici, testuali, extralinguistici, di intenzionalità e pragmatici sorti durante l’esperimento. A seguito di ciò, il terzo capitolo e le conclusioni finali si focalizzeranno sui limiti che compromettono maggiormente le prestazioni dei TA, prendendo come riferimento il linguaggio e le caratteristiche proprie dei testi turistici.
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Mai, Guan Hui Jennifer. "A report on a C-E technical translation project using Google Translate." Thesis, University of Macau, 2018. http://umaclib3.umac.mo/record=b3954279.

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Laird, Eriksson Nickole. "Google Translate in English Language Learning : A Study of Teachers' Beliefs and Practices." Thesis, Högskolan Dalarna, Engelska, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-36878.

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The purpose of this study is to explore upper secondary school English teachers' beliefs and practices for free online machine translation (FOMT) tools. It is believed that students are using these tools, but the focus of this study is to highlight what teachers think and how they are addressing FOMT usage by students. Participants are currently teaching various English levels in upper secondary schools throughout Sweden and have varying degrees of experience. This study includes a brief background of previous studies detailing teachers' attitudes and methods for incorporating machine translation (MT) in their language teaching. The theoretical framework used for this study is language teacher cognition and translation in language teaching. The results reveal that the previous research conducted in this area has not yet influenced teachers' language classrooms methods. Teachers' education and language learning experience may explain this disconnect to current research. There is a common theme that teachers do not mind using FOMT tools in their personal lives but strongly recommend other sources for their students.
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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 this work provides a theoretical background for MT and its evaluation. Chapter 1 deals with the definition of MT and summarizes its history. Moreover, a detailed analysis of the different MT architectures is provided, as well as an overview of the possible application scenarios and the different categories of users. Chapter 2 introduces the notion of quality in the translation field and the main automatic and manual methods applied to MT quality assessment tasks. A comprehensive analysis of some of the most significant studies on neural and phrase-based MT systems output quality is then provided. The second part of this work presents a quality assessment of the output produced by two neural MT systems, i.e. Google Translation and DeepL Translator. The evaluation was performed through manual error annotation based on a fine-grained error taxonomy. Chapter 3 outlines the methodology followed during the evaluation, with a description of the dataset, the neural MT systems chosen for the study, the annotation tool and the taxonomy used during the annotation task. Chapter 4 provides the results of the evaluation and a comment thereof, offering examples extracted from the annotated data set. The final part of this work summarizes the major findings of the present contribution. Results are then discussed, with a focus on their implication for future work.
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Russo, Federica. "Google Translate e Microsoft Translator - Valutazione di due applicazioni per la traduzione automatica del parlato e analisi di una tecnologia in evoluzione." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/10626/.

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This work focuses on Machine Translation (MT) and Speech-to-Speech Translation, two emerging technologies that allow users to automatically translate written and spoken texts. The first part of this work provides a theoretical framework for the evaluation of Google Translate and Microsoft Translator, which is at the core of this study. Chapter one focuses on Machine Translation, providing a definition of this technology and glimpses of its history. In this chapter we will also learn how MT works, who uses it, for what purpose, what its pros and cons are, and how machine translation quality can be defined and assessed. Chapter two deals with Speech-to-Speech Translation by focusing on its history, characteristics and operation, potential uses and limits deriving from the intrinsic difficulty of translating spoken language. After describing the future prospects for SST, the final part of this chapter focuses on the quality assessment of Speech-to-Speech Translation applications. The last part of this dissertation describes the evaluation test carried out on Google Translate and Microsoft Translator, two mobile translation apps also providing a Speech-to-Speech Translation service. Chapter three illustrates the objectives, the research questions, the participants, the methodology and the elaboration of the questionnaires used to collect data. The collected data and the results of the evaluation of the automatic speech recognition subsystem and the language translation subsystem are presented in chapter four and finally analysed and compared in chapter five, which provides a general description of the performance of the evaluated apps and possible explanations for each set of results. In the final part of this work suggestions are made for future research and reflections on the usability and usefulness of the evaluated translation apps are provided.
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Dahlberg, Lina. "Mener les enquêtes ne sont neuf à femjobb : La traduction des phrases nominales suédoises en français par l'outil informatique Google Translate." Thesis, Umeå universitet, Institutionen för språkstudier, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-90610.

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Allansson, Jimmy. "When grundskoleklass becomes mainstream classroom : An investigation of the translation of Swedish compound nouns into English using Google Translate." Thesis, Karlstads universitet, Institutionen för språk, litteratur och interkultur, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-34500.

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The aim of this study was to examine how Swedish compound nouns are translated by the machine translation program Google Translate. In order to conclude what main types of mistranslation occur, different texts were first translated by the program; all compound nouns were then listed and analysed, and the mistranslated compound nouns were categorised in accordance with the manner of mistranslation. The study was also working from a hypothesis that the frequency of a compound would affect the chances of getting a correct translation. To test this hypothesis, queries were run in a Swedish corpus to get an estimation of how frequently used the compounds are. The results show that mistranslations could be categorised into four different types, and that the most common types of mistranslation were omitting part of the compound, and translating reoccurring compounds inconsistently. The hypothesis that compounds with high frequency in the corpus would be correctly translated, while compounds with low frequency would be incorrectly translated, could not be conclusively confirmed or refuted. Although there was some indication of a link between frequency and translation accuracy, the connection was not clear enough to claim that there is a correlation.
Syftet med denna undersökning var att undersöka hur sammansättningar på svenska behandlas av maskinöversättningsprogrammet Google Translate. För att bedöma vilka som var de vanligaste typerna av felöversättningar översattes först olika texter med programmet. Sammansättningarna listades sedan och analyserades, och felöversatta sammansättningar kategoriserades efter typ av felöversättning. Undersökningen utgick vidare från hypotesen att frekvensen av ett sammansatt ord skulle påverka sannolikheten för en korrekt översättning. För att testa denna hypotes gjordes sökningar på orden i en svensk korpus för att få en uppfattning om hur vanligt förekommande sammansättningarna är. Resultaten visar att felöversättningarna kunde kategoriseras som fyra olika typer, och att de vanligaste typerna var att ett led i sammansättningen utelämnades samt att återkommande sammansättningar var inkonsekvent översatta. Hypotesen att sammansättningar med hög frekvens i korpusen skulle bli korrekt översatta och sammansättningar med låg frekvens inkorrekt översatta, kunde inte entydigt bekräftas eller vederläggas. Det fanns vissa indikationer på en koppling mellan frekvens och översättning, dock var dessa inte tydliga nog för att hävda att ett klart samband existerar.
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Qureshi, Karl. "Att maskinöversätta sökfrågor : En studie av Google Translate och Bing Translators förmåga att översätta svenska sammansättningar i ett CLIR-perspektiv." Thesis, Umeå universitet, Sociologiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-131813.

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Syftet med denna uppsats är att undersöka hur väl Google Translate respektive Bing Translator fungerar vid översättning av sökfrågor med avseende på svenska sammansättningar, samt försöka utröna huruvida det finns något samband mellan utfallet och sammansättningarnas komplexitet. Testmiljön utgörs av Europaparlamentets offentliga dokumentregister. Undersökningen är emellertid begränsad till Europeiska rådets handlingar, som till antalet är 1 334 på svenska respektive 1 368 på engelska. Analysen av data har dels skett utifrån precision och återvinningsgrad, dels utifrån en kontrastiv analys för att kunna ge en mer enhetlig bild på det undersökta fenomenet. Resultatet visar att medelvärdet varierar mellan 0,287 och 0,506 för precision samt 0,400 och 0,614 för återvinningsgrad beroende på ordtyp och översättningstjänst. Vidare visar resultatet att det inte tycks finnas något tydligt samband mellan effektivitet och sammansättningarnas komplexitet. I stället tycks de lägre värdena bero på synonymi, och då gärna inom själva sammansättningen, samt hyponymi. I det senare fallet beror det dels på översättningstjänsternas oförmåga att återge lämpliga översättningar, dels på det engelska språkets tendens att bilda sammansättningar med lösa substantivattribut.
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Books on the topic "Google Translate"

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Propertius, Sextus. Elegies: Propertius ; edited and translated by G.P. Goold. Cambridge, Mass: Harvard University Press, 1990.

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P, Goold G., ed. Elegies: Propertius ; edited and translated by G.P. Goold. Cambridge, Mass: Harvard University Press, 1999.

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Propertius, Sextus. Elegies: Propertius ; edited and translated by G.P. Goold. Cambridge, Mass: Harvard University Press, 1990.

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Book chapters on the topic "Google Translate"

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Wallwork, Adrian. "Using Google Translate and Analysing Student- and GT-Generated Mistakes." In English for Academic Research: A Guide for Teachers, 55–68. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32687-0_5.

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Kelsey, Todd. "Going Global: Connecting with People in Other Countries and Languages, with Google Translate and Google Multilingual Chat." In Social Networking Spaces, 467–83. Berkeley, CA: Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-2597-3_18.

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Mraček, David. "Uncovering the Potential of the Google Search Engine for L2 Learning and L2 Translator Training." In Emerging Technologies for Education, 109–21. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38778-5_14.

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Lamichhane, Dev Raj, Janet C. Read, and Zixi You. "Maybe I Can Help? Google as a Translator and Facilitator for an Inter-lingual Children’s Chat Application." In HCI International 2021 - Posters, 208–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78635-9_29.

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Cassin, Barbara. "On Cultural Democracy." In Google Me, translated by Michael Syrotinski. Fordham University Press, 2017. http://dx.doi.org/10.5422/fordham/9780823278060.003.0006.

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The focus of this final chapter is to explore the far-reaching effects of Google on our books and our languages. It looks at the different resistances to Google’s domination from publishers and national libraries, including the attempts to set up competing European digital libraries and search engines. It also looks at the fraught question of copyright and fair use and the limits of Google Translate in a genuinely multilingual approach to culture.
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Halimi, Sonia, and Pierrette Bouillon. "Google translate and BabelDr in community medical settings." In Arabic Translation Across Discourses, 27–44. Routledge, 2019. http://dx.doi.org/10.4324/9781351063388-3.

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"Translator’s Foreword: Why I Translate So Intelligently: Translation Mètis in the Era of Google Translate." In Morphing Intelligence, vii—xii. New York Chichester, West Sussex: Columbia University Press, 2019. http://dx.doi.org/10.7312/mala18736-001.

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Miklosik, Andrej. "Search Engine Marketing Strategies." In Handbook of Research on Entrepreneurship and Marketing for Global Reach in the Digital Economy, 463–85. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6307-5.ch020.

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Ensuring search engine visibility is one of the key tasks of marketers nowadays. Besides regular organic results, other forms of rich content results appear on Google including the Google Answer Box. In this chapter, the author analyzes the factors that determine the chance of a website being excerpted in the Google Answer Box. Moreover, he uses a simulation to examine the most probable weights of three factors on the final rankings within the search engine results page. The created framework for constructing the assessment of factors can be used to develop similar models for different niches and keywords and utilized by organizations from various sectors. Adopting these findings by organizations and including them in their content and marketing strategy will have a positive impact on search visibility and thus translate to efficiency of marketing campaigns.
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Pongthanisorn, Goragod, Waranrach Viriyavit, Thatsanee Charoenporn, and Virach Sornlertlamvanich. "Visual Programming for Artificial Intelligent and Robotic Application (VPAR) Framework." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia210477.

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Computer programming is popularized in 21st century education in terms of allowing intensive logical thinking for students. Artificial Intelligent and robotic field is considered to be the most attractive for programming today. However, for the first-time learners and novice programmers, they may encounter a difficulty in understanding the text-based style programming language with its special syntax, sematic, libraries, and the structure of the program itself. In this work, we proposed a visual programming environment for artificial intelligent and robotic application using Google Blockly. The development framework is a web application which is capable of using Google Blockly to create a program and translate the result of visual programming style to conventional text-based programming. This allows almost instant programming capability for learners of programming in such a complex system.
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Domanchin, Morgane. "A case study of a learner’s use of an online translator as a cognitive tool in a SCMC context." In CALL and complexity – short papers from EUROCALL 2019, 113–17. Research-publishing.net, 2019. http://dx.doi.org/10.14705/rpnet.2019.38.995.

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This study explores a language learner’s screen while interacting from a desktop videoconferencing device as part of an intercultural telecollaboration exchange that connected teacher-trainees and French learners. Communicative tasks involving opinion exchanges require from language learners simultaneous speaking and listening comprehension skills, which may prompt linguistic difficulties. To compensate for their weaknesses, learners had access to online resources exposing them to various and complex language use. Based on Jonassen’s (1992) work on ‘cognitive tools’ as intelligent resources that contribute to knowledge construction, the author draws on multimodal interaction analysis to question the uses of an automatic online translator in the context of Synchronous Computer Mediated Communication (SCMC). This study illustrates a learner’s technical autonomy using Google Translate (GT) to search for vocabulary while interacting with his interlocutors. It reports the learner’s emergence of a linguistic need which is followed by a search for vocabulary leading in some cases to the searched translation’s integration within the pedagogical interaction. This study raises cognitive challenges that such a practice presents for language learning.
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Conference papers on the topic "Google Translate"

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Budiharjo, Bayu. "Google, Translate This Website Page-Flipping through Google Translate's Ability." In Fourth Prasasti International Seminar on Linguistics (Prasasti 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/prasasti-18.2018.84.

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Lunić, Darija, Nemanja Stanišić, Angelina Njeguš, and Ivana Đerić. "Google Translate Accuracy Evaluation." In Sinteza 2020. Beograd, Serbia: Singidunum University, 2020. http://dx.doi.org/10.15308/sinteza-2020-80-85.

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Lee, Dickson T. S., Zhi Quan Zhou, and T. H. Tse. "Metamorphic Robustness Testing of Google Translate." In ICSE '20: 42nd International Conference on Software Engineering. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3387940.3391484.

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Rosaria, Stefani, and Rati Riana. "Weaknesses of Translation Result Using Google Translate." In Proceedings of the 2nd International Seminar on Translation Studies, Applied Linguistics, Literature and Cultural Studies, STRUKTURAL 2020, 30 December 2020, Semarang, Indonesia. EAI, 2021. http://dx.doi.org/10.4108/eai.30-12-2020.2311244.

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Wirantaka, Andi, and Mahdiana Syahri Fijanah. "Effective Use of Google Translate in Writing." In International Conference on Sustainable Innovation Track Humanities Education and Social Sciences (ICSIHESS 2021). Paris, France: Atlantis Press, 2022. http://dx.doi.org/10.2991/assehr.k.211227.003.

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Klyuev, V., and Y. Haralambous. "Query translation for CLIR: EWC vs. Google Translate." In 2012 IEEE International Conference on Information Science and Technology (ICIST). IEEE, 2012. http://dx.doi.org/10.1109/icist.2012.6221738.

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Khairani, Anisya Firdha, Pepen Permana, and Irma Permatawati. "Google Translate in Perceptions of German Language Students." In 4th International Conference on Language, Literature, Culture, and Education (ICOLLITE 2020). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.201215.011.

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Duarte, Jane. "GOOGLE TRANSLATE IN THE TRANSLATION CLASSROOM: NEW CHALLENGES, NEW LITERACIES." In 13th International Conference on Education and New Learning Technologies. IATED, 2021. http://dx.doi.org/10.21125/edulearn.2021.2530.

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Nugraha, Deden Novan Setiawan. "Grammatical and Diction Inaccuracy in English—Indonesian Translation on Google Translate." In Proceedings of the International Conference on Educational Psychology and Pedagogy - "Diversity in Education" (ICEPP 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200130.075.

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Wijayanto, Pikir Wisnu. "The Translation Analysis of English Imperatives into Javanese by Google Translate." In Borneo International Conference On Education And Social. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0009018902100217.

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