Academic literature on the topic 'Google Translate'

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.

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.

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.

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.

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.

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.

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.<br>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.

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.