Dissertations / Theses 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.
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.

The English translation of the Swedish compound fönsterbräda into windowsill, or the proper noun Danmark into Denmark makes perfect sense. But how about the compound fossilbränslefri as simply fossil fuel or the name Mälaren as Lake?  All four of these translations have been produced with the help of automatic machine translation. The aim of this paper is to present the expanding field of application of machine translation and some issues related to this type of translation. More specifically, the study has looked at Google Translate as one of the most commonly used machine translation systems online, and how it responds to the two linguistic categories that were selected for this small study: compound nouns and proper nouns. Besides analyzing these categories, two different text types were chosen: general information articles from a local authority website (Stockholm City) and patent texts, both of which belong to the expanding field of application of Google Translate. The results of the study show that in terms of compound nouns, neither of the text types proved to be significantly better suited for machine translation than the other and neither had an error rate below 20 %. Most of the errors related to words being erroneously omitted in the English output and words which were incorrectly translated in relation to context. As for proper nouns, the patent texts contained none and subsequently no error analysis could be made, whereas the general information articles included 76 proper nouns (out of a total word count of 810). The most prominent error related to the Swedish version not being maintained in the English output where it should have been, e.g. translating Abrahamsberg as Abraham rock. The errors in both of the linguistic categories had varying impact on the meaning of the texts, some of which distorted the meaning of the word completely, and some which were of minor importance. This factor, along with the fact that the reader of the text influences how the comprehension level of the text is perceived through their language and subject knowledge, makes it difficult to evaluate the full impact of the various errors. It can, however, be said that patent text could pose as a better option for machine translation than general information articles in relation to proper nouns, as this text type is likely to contain no or very few proper nouns.

Bakgrund: En observation under verksamhetsförlagd utbildning har varit att Google Translate, ett digitalt översättningsverktyg, har använts som hjälpmedel för att försöka förmedla information till patienter. Effektiv kommunikation mellan sjuksköterska och patient är en grundläggande förutsättning för sjuksköterskans arbete och för personcentrerad vård. På grund av språkförbistringar uppstår det ofta problem i kommunikation med patienten.Syfte: Syftet med denna studie var att undersöka om och i vilken utsträckning sjuksköterskor i slutenvården på sjukhuset i fråga använder sig av digitala översättningsverktyg i kommunikation med patienter.Metod: En tvärsnittsstudie genomfördes med hjälp av webbenkät på ett stort sjukhus i södra Sverige. Populationen bestod av 279 sjuksköterskor, 76 av dessa besvarade enkäten.Resultat: Undersökningen visade att 61,8 procent av deltagarna (n= 47) har någon gång använt digitala översättningsverktyg, nästan uteslutande Google Translate, i kommunikationen med patienter. De vanligaste situationerna då det har använts var vid smärtskattning och informationsförmedling.
Background: An observation during the clinical practice has been that Google Translate, a digital translation tool, was used as a means to inform patients. Effective nurse-patient communication is a basic qualification for the nurse ́s work and for patient-centered care. Due to language barriers, problems often occur in communication with the patient.Aim: The aim of this study was to find out if, and to what extent, nurses working in hospital care at the hospital in question use digital translation tools when communicating with patients.Method: A cross-sectional study was conducted at a large hospital in southern Sweden through an online questionnaire.The population consisted of 279 nurses, 76 of these filled out the questionnaire.Results: The study showed that 61,8 percent of the participants (n=47) have at some point used digital translation tools, especially Google Translate, when communicating with patients. The most common situations this tool was used in was during pain assessment and when delivering information.

Automatic translations, or machine translations, get more and more advanced and common. This paper aims to examine how well Google Traduction works for translating an ideological text. To what extent can a computer program interpret such a text, and render the meaning of complex thoughts and ideas into another language ? In order to study this, UNESCOS World Report Investing in Cultural Diversity and Intercultural Dialogue has been translated from french to swedish, first automatically and then manually. Focusing on denotations, connotations, grammar and style, the two versions have been analysed and compared. The conclusion drawn is that while Google Traduction impresses by its speed and possibilites, editing the automatically translated text in order to correctly transmit the mening and the message of the text to the target language reader, would probably be a more time-consuming process than writing a direct translation manually.

Работа посвящена сравнению качества перевода технического текста с английского языка на русский, полученного с помощью различных систем машинного перевода (СМП), на примере научной статьи металлургической тематики “Fluid Dynamics Studies of Bottom-blown and Side-blown Copper Smelting Furnaces”. В первой части работы рассматриваются общие вопросы машинного и технического перевода: приводятся понятия машинного перевода и технического перевода, определяются основные способы и алгоритмы работы СМП, выделяются основные особенности и проблемы технического перевода. Особое внимание уделяется выявлению функциональных возможностей наиболее популярных сервисов машинного перевода, к которым относятся такие СМП как Google Translate, Яндекс Переводчик, Bing Microsoft Translator, SYSTRAN Translate, PROMT.One. Во второй части работы раскрываются особенности металлургической терминологии и специфика ее заимствования, разрабатывается методика оценки качества перевода технического текста металлургической направленности, проводится апробационное исследование переводов, выполненных с помощью различных систем машинного перевода и определяются перспективы использования СМП в металлургической отрасли. Большое внимание уделяется оценке качества переводов по представленным методикам, при этом все результаты приводятся в виде таблиц с указанием количества ошибок и итоговых баллов. Результаты исследования могут быть использованы на различных предприятиях металлургического сектора при работе с документацией на иностранных языках.
This paper is devoted to comparison of translation quality obtained as a result of using machine translation (MT) systems to translate technical documents from English into Russian in the case of a metallurgical article “Fluid Dynamics Studies of Bottom-blown and Side-blown Copper Smelting Furnaces”. The first part of the paper covers general issues of machine and technical translation, including concepts of machine and technical translation, the main operation methods and algorithms, and the main features of technical translation. Particular attention is paid to identification of core functionality of the most popular machine translation systems, which include Google Translate, Yandex Translate, Bing Microsoft Translator, SYSTRAN Translate, PROMT.One. The second part of the paper reveals the main features of metallurgical terminology and the specifics of its naturalization. It also contains several translation quality assessment methodologies and includes an analysis of machine translation quality. Moreover, it features the main prospects for using MT systems in metallurgy. Much attention is paid to translation quality assessment on methodologies presented in the paper. All the results are presented in the form of tables with the number of errors and final scores for each MT system. The results of the study may be used at various metallurgical enterprises working with documentation in foreign languages.

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 professionali. Vengono delineati gli aspetti linguistici per poi fornire una breve panoramica delle iniziative che sono state proposte nel contesto italiano e internazionale per promuovere l’uso del genere femminile nella lingua ed evitare di usarla in maniera sessista e non inclusiva. Nel capitolo III, dopo aver esposto nel dettaglio la metodologia impiegata degli studi precedenti, si presenta la struttura frasale ideata per condurre lo studio di caso. Partendo dall’elaborazione dei dati statistici sul numero di donne per ogni occupazione, si giunge alla selezione delle professioni da impiegare nello studio. Vengono inoltre illustrati gli strumenti utilizzati nell’analisi basata su corpora che verrà condotta nel capitolo IV, dove si presenta l’analisi degli output forniti da due sistemi di traduzione automatica, DeepL e Google Translate, nella combinazione linguistica inglese-italiano. L’analisi dettagliata di tutti gli aspetti della struttura frasale è corredata da tabelle e grafici esplicativi, inoltre sono presenti approfondimenti sulle traduzioni di alcune professioni di particolare rilevanza. I risultati dell’analisi verranno infine discussi in maniera approfondita, ipotizzando infine le prospettive future degli studi in questo ambito.

Machine translation (MT) is experiencing a renaissance. On one hand, machine translation is becoming more common and used in ever larger scale, on the other hand many translators have an almost hostile attitude towards machine translation programs and those translators who use MT as a tool. Either it is assumed that the MT can never be as good as a human translation or machine translation is viewed as the ultimate enemy of the translator and as a job killer. The article discusses with various examples the limits and possibilities of machine translation. It demonstrates that machine translation can be better than human translations – even if they were made by experienced professional translators. The paper also reports the results of a test that showed that translation customers must expect that even well-known and expensive translation service providers deliver a quality that is on par with poor MT. Overall, it is argued that machine translation programs are no more and no less than an additional tool with which the translation industry can satisfy certain requirements. This abstract was also – as the entire article – automatically translated into English.

This thesis aims to analyze the supposed inevitability of a breakthrough in machine translation and the role that this breakthrough will play in the evolution of translation companies. It will analyze the changes that are happening and what repercussions those changes will have on the decisions made by students, professionals, agencies, and institutions over the next twenty years. This paper will be divided into three main sections: The first part will provide a background of today’s translation industry and consider the advent of machine translation in translation agencies and its continuous developments. In the second part of this essay, I will illustrate how I carried out my research inside Global Voices - a translation agency based in Stirling, Scotland, in which I have interned as Project Manager in December 2018 - to understand what use the translation agency makes of machine translation, also conveying my colleagues’ thoughts about it. The conclusion will recapitulate the topics approached, revolve around the main findings of this study and try to foresee what translators should expect from the future, how in my opinion they should deal with the changes the future will bring.

Bien qu’ils soient largement utilisés dans le domaine, les mesures vibratoires classiques présentent plusieurs limites. A la base, l’analyse vibratoire ne peut identifier qu’environ 60% des défauts qui peuvent survenir dans les machines. Cependant, les principaux inconvénients des mesures de la vibration sont l’accès difficile au système de transmission afin d’y placer le capteur ainsi que le coût conséquent de la mise en œuvre. Ceci résulte en des problèmes de sensibilité relatifs à la position de l’installation et ceux de difficulté pour distinguer la source de vibration à cause de la diversité des excitations mécaniques qui existent dans l’environnement industriel.Par conséquent, l’analyse des signatures du courant électrique des moteurs s’impose comme une alternative prometteuse à l’analyse vibratoire et a donc fait l’objet d’une attention grandissante au cours des dernières années. En effet, l’analyse des signatures électriques a l’avantage d’être une méthode techniquement accessible, non-intrusive au système et peu coûteuse. Les techniques basées sur le courant et la tension ne requièrent que les mesures électriques du moteur qui sont souvent déjà surveillées pour le contrôle et la protection des machines électriques. Ce processus a été principalement utilisé pour la détection des défauts de moteur tels que la rupture de barres du rotor et les défauts d’excentricité ainsi que les défauts de roulements. En revanche, très peu de recherches concernent la détection des défauts en utilisant l’analyse du courant. En outre, les signaux électriques triphasés sont caractérisés par des représentations géométriques particulières liées à leur forme d’onde qui peuvent servir en tant qu’indicateurs différents offrant des informations supplémentaires. Parmi ces indicateurs géométriques, les transformées de Park et de Concordia modélisent les composantes électriques dans un repère bidimensionnel et toute déviation par rapport à la représentation d’origine indique l’apparition d’un dysfonctionnement. Aussi, les équations différentielles de Frenet-Serret représentent la trajectoire du signal dans un espace euclidien tridimensionnel et indiquent ainsi tout changement dans l’état du système. Bien qu’ils aient été utilisés pour les défauts de roulements, ces indicateurs n’ont pas été appliqués dans la détection des défauts d’engrenages en utilisant l’analyse des signatures des courants électriques. D’où l’idée novatrice de combiner ces indicateurs avec des techniques de traitement de signal, ainsi que des techniques de classification pour le diagnostic des engrenages en utilisant l’analyse des signatures de courant et de tension du moteur électrique.Ainsi, dans ce travail, on propose une nouvelle approche pour le diagnostic des défauts d’engrenages en utilisant l’analyse des courants et des tensions électriques du stator de la machine et ceci en se basant sur un ensemble d’indicateurs géométriques (Transformées de Park et de Concordia ainsi que les propriétés du repère Frenet-Serret). Ces indicateurs font partie d’une bibliothèque de signatures de défauts qui a été construite et qui comprend également les indicateurs classiques utilisés pour un large éventail de défauts. Ainsi, un algorithme combine les acquisitions expérimentales des signaux électriques à des méthodes de traitement de signal avancées (décomposition modale empirique,…). Ensuite, celui-ci sélectionne les indicateurs les plus pertinents au sein de la bibliothèque en se basant sur les algorithmes de sélection de paramètres (sélection séquentielle rétrograde et analyse des composantes principales). Enfin, cette sélection est utilisée pour la classification non-supervisée (K-moyennes) pour la distinction entre l’état sain et l’état défaillant
Although they are widely used, classical vibration measurements have several limitations. Vibration analysis can only identify about 60% of the defects that may occur in mechanical systems. However, the main drawbacks of vibration measurements are the difficult access to the transmission system in order to place the sensor as well as the consequent cost of implementation. This results in sensitivity problems relative to the position of the installation and the difficulty to distinguish the source of vibration because of the diversity of mechanical excitations that exist in the industrial environment.Hence, the Motor Current Signatures Analysis (M.C.S.A.) represents a promising alternative to the vibration analysis and has therefore been the subject of increasing attention in recent years. Indeed, the analysis of electrical signatures has the advantage of being a technically accessible method as well as inexpensive and non-intrusive to the system. Techniques based on currents and voltages only require the motor’s electrical measurements which are often already supervised for the purposes of the control and the protection of the electrical machines. This process was mainly used for the detection of motors faults such as rotor bars breakage and eccentricity faults as well as bearings defects. On the other hand, very little research has been focused on gear faults detection using the current analysis. In addition, three-phase electrical signals are characterized by specific geometric representations related to their waveforms and they can serve as different indicators providing additional information. Among these geometric indicators, the Park and Concordia transforms model the electrical components in a two-dimensional coordinate system and any deviation from the original representation indicates the apparition of a malfunction. Moreover, the differential equations of Frenet-Serret represent the trajectory of the signal in a three-dimensional euclidean space and thus indicate any changes in the state of the system. Although they have been previously used for bearing defects, these indicators have not been applied in the detection of gear defects using the analysis of electrical current signatures. Hence, the innovative idea of combining these indicators with signal processing techniques, as well as classification techniques for gears diagnosis using the three-phase motor’s electrical current signatures analysis is established.Hence, in this work, a new approach is proposed for gear faults diagnosis using the motor currents analysis, based on a set of geometric indicators (Park and Concordia transforms as well as the properties of the Frenet-Serret frame). These indicators are part of a specifically built fault signatures library and which also includes the classical indicators used for a wide range of faults. Thus, a proposed estimation algorithm combines experimental measurements of electrical signals with advanced signal processing methods (Empirical Mode Decomposition, ...). Next, it selects the most relevant indicators within the library based on feature selection algorithms (Sequential Backward Selection and Principal Component Analysis). Finally, this selection is combined with non-supervised classification (K-means) for the distinction between the healthy state and faulty states. It was finally validated with a an additional experimental configuration in different cases with gear faults, bearing faults and combined faults with various load levels

This master's thesis describes process of design and development of a mobile system for travelling support. Application named TravelHelper is developed for Android operating system therefore is implemented in Java programing language. In thesis's text is described used platform and its primary construction blocks. Main function of application is a journeys' diary, which allows storing activities of a trips. Application also allows backing up and sharing journeys on a social networks. Other functions of the application are searching for interesting places nearby, manager of travel expenses, translator, currency converter, and a packing list.

This study focuses on and tries to identify areas where machine translation can be useful by examining translated fictional and non-fictional texts, and the extent to which these different text types are better or worse suited for machine translation.  It additionally evaluates the performance of the free online translation tool Google Translate (GT). The BLEU automatic evaluation metric for machine translation was used for this study, giving a score of 27.75 BLEU value for fictional texts and 32.16 for the non-fictional texts. The non-fictional texts are samples of law documents, (commercial) company reports, social science texts (religion, welfare, astronomy) and medicine. These texts were selected because of their degree of difficulty. The non-fictional sentences are longer than those of the fictional texts and in this regard MT systems have struggled. In spite of having longer sentences, the non-fictional texts got a higher BLUE score than the fictional ones. It is speculated that one reason for the higher score of non-fictional texts might be that more specific terminology is used in these texts, leaving less room for subjective interpretation than for the fictional texts. There are other levels of meaning at work in the fictional texts that the human translator needs to capture.

Google Translate helps people around the world to translate from one language to another, and translates about 100 billion words every day. The translation is used for all types of information, for essays, on websites, social media or for every day communication. Companies and organizations can reach people all over the world by offering machine translation on their websites. This means that companies and organizations can spread their messages and their products to a much larger group of people. However, in order for the information to be correct, there must be an availability regardless of language. It is therefore interesting to find out if the usefulness of Google Translate as machine translation can affect the availability of websites. The purpose of the study is to find out if Google Translate as machine translation can affect a website's usefulness in translating the information provided by the website. The purpose of the study is limited by merely examining in what ways the usability and availability of the information "About Us" on government and municipal websites is affected by Google Translate as machine translation. The method used in the study is usability tests where a think aloud observation was conducted with study participants who tested the websites using task scenarios. The result of our study showed that Google Translate is useful as machine translation on websites. In conclusion, however, we discussed whether the results could have been affected due to the delimitations we made, such as language selection, websites and method.

This research investigated the feasibility of South African translations of Dewey Decimal Classification (DDC). The study provides an introductory overview of DDC throughout the world, followed by its use in South Africa. The introduction highlights shortcomings and possible solutions – of which translations seem to be the most ideal. This research involved a critical analysis of the literature on DDC translations, a documentary analysis and technology-based research in the form of Google translations and evaluation of parts of Abridged Edition 15 of DDC. The critical analysis of the literature and the documentary analysis identified problems relating to translations, how translations deal with shortcomings in DDC, the fact that no literature exists on multilingual translations, and the process of translations (including the fact that this is an expensive endeavour). It also revealed information about sponsorship and the mixed translation model. The technology-based research, using Google Translate for translations of parts of Abridged Edition 15 and the subsequent evaluation of these translations indicated that Google translations were comprehensive and needed minimum editorial effort. Further to this it paved the way for describing a possible workflow for South African translations and indicated that the parts already translated as well as further Google translations can expedite the translation process. A model for South African translations, based on only the cost of the Pansoft translation software was proposed. The mixed model approach, where some languages are used as main languages (schedules, Relative Index terms and the like) and others for Relative Index terms only, was deemed the most appropriate in the South African context. This led to the conclusion that DDC translations into ten of the official South African languages are indeed feasible. The research supports translations that keep the integrity of DDC intact, with possible expansions based on literary arrant. It is important, though, to get the support of the South African library community and authoritative bodies such as the National Library of South Africa and/or the Library and Information Association of South Africa (LIASA) to negotiate and sign a contract for these translations.
Information Science
D. Litt. et Phil. (Information Science)

碩士
輔仁大學
跨文化研究所翻譯學碩士班
100
Frequent interaction and trade between countries have fueled the need for instant and large-scale translation, which triggers the emergence of machine translation (MT), and because of the ubiquitous Internet, translation services have been widely available in recent years. However, even though MT (or online translation services) is fast, convenient, easy to use, and even free of charge, it still cannot satisfy needs of all kinds. For MT to be fully accepted, translation quality has always been the biggest obstacle yet to be overcome. This present study examines a representative online translation service, Google Translate (GT), and its Chinese translation output. With a cell phone user manual as source text, the study analyzes its target text from lexical and syntactic perspectives, followed by a brief summary of the pros and cons of GT. Based on these linguistic characteristics collected from GT output, the study concludes with discussions and suggestions on how to use GT effectively so that the benefits of using it can be maximized. A thorough translation analysis finds GT prone to make certain lexical mistakes, categorized in this study as polysemy, semantic deviation, and word choice. Collocation in the source text is probably the key to producing good GT translation. Syntactically speaking, GT tends to translate sentences following their syntactic order; therefore, GT is most suitable for translating sentences with a clear and simple structure, among which imperative sentences, which have a verb phrase as the core, stand out from the rest. Furthermore, post-modifiers are usually the challenge GT fails to conquer. Finally, to make full use of GT, users should get used to the non-linear reading path caused by the uneven translation quality among sentences. Also, users should avoid translating an article all at one time; instead, breaking the article into sentences or smaller syntactic units would help improve translation quality and thus increase the effectiveness of using GT.