Google Translatation Versus Manual Translation Essay Example

the very idea of translation and dissects its different forms. It also delves into the specifics of Google Translate and juxtaposes it with manual translation, revealing notable differences between them. Additionally, this study aims to understand how both these methods influence students' English-to-Indonesian translations. This research employs qualitative methodology utilizing descriptive techniques. By leveraging theoretical data accrued from diverse sources like books, articles, and other related literature, our goal is to comprehensively illuminate the realm of translation while exploring the trend towards using Google Translate.

This paper utilizes the technique of content evaluation to analyze the information; this involves scrutinizing and incorporating data in accordance with the context of this study. The latter part is primarily an in-depth theoretical exploration of translation, especially its specific definition. As Brislings (1976:1) broadly defines it, translation signifies transferring ideas and notions from one language (the origin) to another (the destination), regardless if these languages are written or spoken, have a standardized spelling system or not, or use signs like those used by people who are hearing impaired.

According to his definition, translation encompasses a broad range of situations. This includes transferring thoughts and ideas into sign language for the deaf or translating into a less common language. The dictionary defines translation as the process of converting one's own or another person's language. This definition encompasses a wide range of circumstances, such as translating poetry or expressing emotions through music. Schulte and Biguenet (1992:145) refer to this situation as transmutation, which is the interpretation of verbal signs using nonverbal sign systems.

In addition to oral and written translation, the process of translating from archaic to contemporary

language was also incorporated. Tonus's interpretation of translation (1997:27) suggests that it can be perceived as (1) a theoretical phenomenon, (2) a subject for research, and (3) an exercise or activity involving this phenomenon. This study embraces this understanding, offering a more lucid view of translation. Various terminologies are utilized to describe translation as the theory related to translated phenomena. As a subject of investigation, translation can be classified into three distinct groups: translation as language-related phenomena, non-language-related phenomena, and both language- and non-language-related phenomena. Translation as an independent phenomenon can further be divided into three types: intralingua, interlingua and inter-semiotic translations - as stated by Jacobson (cited in Tou 1997:13). A visual illustration of these classifications is provided below. Nida and Taber's proposition (1969:12) indicates that the act of translating requires one to create the most accurate equivalent in the target language reflecting both meaning and style originally present in the source text.

According to translators, they should use the closest natural equivalent in either meaning or style of the receptor language. In other words, the outcome of translation should not sound like a translation while maintaining the source language's meaning. A similar definition of translation is mentioned by Newmark (1988:32), who states that translation is the overarching term for converting the meaning of any source language utterance to the target language.

B. Types of Translation
According to Larson (1984:15), translation is classified into two main types: form-based and meaning-based translation.

Form-based, or literal translation aims to retain the structure of the original language. On the other hand, meaning-based or idiomatic translation prioritizes conveying the essence or core message of the source text

in a more fluid manner in the recipient language.

Interlinear translations exemplify an entirely literal translation methodology. This is beneficial for purposes such as examining linguistic characteristics of a text. However, if one's intent is to comprehend what the source material means in another language, literal translations might not be suitable. They can often come across as nonsensical and lack meaningful communication (Larson 1984:15).

Literal translations are comprehensible when there's a parallelism in grammatical structures between two languages. However, truly verbatim translations are rare apart from interlinear variants. Many translators who seem to adhere to literal translation tend to offer slightly modified versions instead.

Larson (1984:16) suggests that for a translation to be effective, it needs to modify the sequence and syntax to align with the target language's favored sentence formation. However, even if a literal translation of lexical components is used, the resulting text may not feel natural. Larson (1984:16) further clarifies that for an authentically idiomatic rendition, not only should syntactic structures be adapted but also the choice of lexical elements should match the natural usage of the target language. The ultimate goal is for such a translation to be indistinguishable from an original piece in its fluency.

The content implies that a proficient translator aims to deliver translations that are suitable and instinctive for the target language. The objective is to attain idiomatic translation, but it's often difficult to maintain this consistently in practice. Translations typically include both literal and idiomatic phrases, ranging from very literal to slightly altered literal, near idiomatic, and completely idiomatic. Sometimes, translations might even lean towards excessively liberal interpretations as illustrated below (Larson,

1984:17).

Illustration 3. The primary goal of a translator is to evade excessively liberal interpretations, which are generally deemed unsuitable for most uses. These overly loose translations are categorized based on three properties: 1) their inclusion of extra data not found in the original text, 2) their modification of the source language (SL) message, and 3) their misrepresentation of the SL text's historical and cultural context. Occasionally, these overly flexible translations may be created for comedic effect or to elicit specific responses from individuals who speak the target language (Larson, 1986:17).

In terms of extent, Catford (1965:21) categorizes translation into full, total, and restricted translation. Full translation involves translating the entire text, replacing every part of the source language text with text material. Total translation falls under the levels of translation category, while restricted translation falls under ranks bound and unbounded translation.

According to Catford (1965:21), a text refers to any spoken or written language that is being discussed. Depending on the circumstances, a text can be a whole library of books, a single volume, a chapter, a paragraph, a sentence, a clause, etc. In partial translation, certain parts of the source language (SL) text are not translated and are instead transferred directly to the target language (TL) text. This approach is not typically used in literal translation as it involves leaving some SL lexical items untranslated. In a total translation, both the grammar and vocabulary of the SL are replaced with their equivalent in the TL. This may also involve replacing the phonology/graphology of the SL with the nonequivalent phonology/graphology of the TL. On the other hand, in restricted translation, only

certain levels of the textual material are replaced with their equivalent in the TL. This can be done either at the phonological or graphological level, or at only one of the two levels of grammar and vocabulary. Rank-bound translation specifically focuses on selecting TL equivalents for certain ranks in the hierarchy of grammatical units, often at the word or morpheme rank. The process of selecting equivalents at different ranks is known as unbounded translation.

Sometimes, between large units than the sentence. According to Brislin (1976:3-4), translation can be categorized into four types for different purposes. These types include: a) Pragmatic translation which focuses on accurately conveying the information intended in the source language without being concerned with other aspects of the original language version. A clear example of pragmatic translation is translating instructions for machine repair.

To print photos and images, using superior resolution paper, shiny photographic paper, or glossy photo film is recommended. These mediums provide improved color accuracy and vibrant colors contrasted with ordinary paper. Moreover, the process of aesthetic-poetic translation includes taking into account the sentiments and emotions present in the original narrative, its unique aesthetic form by the author and any meaning communicated in its message.

The translation of sonnet, rhyme, heroic couplet, dramatic dialogue, and novel are examples of this type. For instance, the rising sun is discovered to not actually be the rising sun; rather, it is the world that revolves around it. Similarly, the bachelor is not truly a bachelor; instead, he is the flower that believed he was deceitful. The love that shines collides with the lust and desire that she fears. The bachelor

then ascends to the heavens in order to obtain dice to present before her eyes. However, both he and she perish. If we are unable to bid farewell face to face.

Even though there's no cause for sadness, I'm engulfed by a desire to weep. As you ascend towards the vast skies, leaving me in solitude on this planet. The once softly murmured comforting lullabies now exist only as memories of bygone times.

The aim of ethnographic translation is to accurately depict the cultural setting across both original and translated languages. These translations should consider not just literal words but also their cultural meanings. A typical example includes differentiating between "yes" and "yea" within American English.

Conversely, linguistic translation too carries its own substantial importance.

The narrative emphasizes the resemblances in morphemes' connotations within the original language and its grammatical structure. This is noticeable in languages applied to computer programming and machine translation. Machine Translation (MT) refers to a procedure where a software scrutinizes an origin text, attempting to create a target text autonomously. In practice though, human intervention becomes needed for pre-editing and post-editing tasks. When correctly managing terminology, making the initial text ready for machine translation through pre-editing, and enhancing the machine's output with a human translator’s help during post-editing - commercial MT utilities can yield worthwhile results. This is particularly applicable if the MT system operates alongside a translation-memory or globalization-management mechanism. Common examples of MT are freely available online via platforms like Google Translate, Babel Fish, Babylon, and StarDict providing rudimentary translations that generally convey the source material's intent under favorable conditions. Furthermore, firms such as Ectaco

manufacture handheld gadgets offering MT services.

The use of unedited machine translation alone fails to acknowledge that understanding human language relies on context and necessitates human comprehension to accurately interpret the original text. While it is true that even translations created solely by humans can contain errors, it is crucial for machine-generated translations to undergo review and editing by a human in order to guarantee usefulness for humans and achieve high-quality translations suitable for publishing.

Claude Piron proposes that machine translation simplifies the basic tasks of a translator's work, with the more complex and time-intensive duties often requiring thorough research to clarify uncertainties in the original text. The need for such clarity arises from both grammatical and lexical needs of the destination language. This groundwork is vital prior to pre-editing the text, which aids in feeding necessary data into machine translation software ensuring coherent results.

According to Brislin (1976:3-4), there are two main types of translation based on the text being translated: factual translation and literary translation. Factual translation focuses on conveying information accurately without involving the translator's emotions or feelings. It is used for translating scientific fields, reports, newspapers, and similar texts. On the other hand, literary translation involves the translation of artistic works and requires the translator to incorporate their emotions and feelings. This type of translation is subjective and includes poems, drama, novels, etc.

According to Brislin (1976:3-4), translators can be categorized as bounded or unbounded based on their translation method. Bounded translation refers to the translation in which the translator maintains the original form of the text and translates it in one rank, often in an interlinear

manner. This is done to preserve the original style of the source text. On the other hand, unbounded translation allows the translator to freely move between different forms. This is done when only the information is important in the translation and there is no significance in maintaining the form. Furthermore, Google Translate can be defined as...

Google Inc. offers a free tool known as Google Translate that aids in translating text between various languages. Until October 2007, this service utilized a translator powered by SYSTRAN for all languages, excluding Arabic, Chinese and Russian – the same system used by Babel Fish, AOL and Yahoo. However, due to rampant misuse causing significant financial strain, Google on May 26th , 2011 decided to cease providing the Google Translate API from December 1st of the same year. This decision sparked criticism from developers along with skepticism over the reliability of Google APIs within their applications. Nevertheless, following public outcry voiced on June 3rd of that year; they reversed their plan to shut down the Translate API and instead unveiled plans to offer its premium version. It's worth mentioning that this service has specific restrictions such as limits on paragraphs or technical terms that can be translated.

This function enables you to input search queries in a particular source language and translate them into your chosen target language. Similarly, it helps you understand the translated results from the preferred target language in your native language. Particularly for technical terminologies, users of specific languages are encouraged to propose alternate translations that could be incorporated into future improvements of the translation process. By entering text in an unfamiliar language

and selecting "Detect Language", not only will it identify this particular tongue but also automatically convert it into English.

The main page of the English Wikipedia, when interpreted into Portuguese via Google Translate, encounters some restrictions. Despite its ability to help users grasp the general gist of text in a different language, it doesn't always provide accurate translations. The results are better for some languages compared to others. Notably, Google Translate exhibits impressive performance while translating from European Union languages into English.

Studies carried out in 2010 confirmed the reliability of French to English translations. Likewise, research in 2011 and 2012 verified the substantial accuracy of Italian to English conversions. However, it was noted that rule-based machine translations function better with shorter texts, a fact particularly pertinent for Chinese to English translation. Furthermore, scripts such as Greek, Devanagari, Cyrillic, and Arabic can be automatically converted into their phonetic equivalents using the Latin alphabet.

Add-ons for Firefox and Google Chrome are available which connect to the Google Translate service, providing an easy method of translation. Furthermore, this translate feature is naturally built into the standard Google Chrome browser for seamless webpage translations. Similarly, Android users have access to a free application of Google Translate that operates in a comparable way as its web browser counterpart.

The main functionalities of Google's Android translation app, "SMS translation" and "History," were introduced during its alpha testing phase in early 2011. The application debuted Conversation Mode for translations between English and Spanish, streamlining communication among users who spoke different languages. By October of the same year, an additional 14 languages were included in this feature. Currently,

the app allows voice input for 15 out of its total supported 53 languages. It is available for download from the Android Market on devices running on Android version 2.1 or higher by searching for "Google Translate".

Google initially launched Google Translate in January 2010, and subsequently released an improved version (latest model: 2.0.0 build 42) on January 12, 2011. In August 2008, a Google Translate HTML5 web application was designed exclusively for iOS users who use iPhone and iPod touch devices. The official iOS app for Google Translate came out later on February 8, 2011. This app allows users to employ voice commands in up to15 languages and offers translations in more than 50 languages. Moreover, it has a feature that enables the vocalization of translations in as many as23 different languages.

The creator of Google Translate's framework, Franz Josef Och, employed a statistical approach in its design as opposed to the traditional rule-based techniques. He is known for his critique on rule-based algorithms and preference towards statistical methods. The technique employed by Google Translate is called statistical machine translation, a concept conceived by Och himself. In 2003, he claimed victory in the DARPA competition for rapid machine translation and presently heads Google's machine translation group.

Google's translation approach does not directly convert from one language (L1) to another (L2). Instead, it typically transitions from L1 to English (EN), then moves on to L2. This process could cause errors in translations due to the inherent ambiguity of languages such as English that heavily depend on context. For instance, when translating the French word "vous" into Russian, Google initially converts it as

"you" in English. However, its exact meaning may vary in Russian and could be "?? OR B?/??". Employing a unique artificial language as a bridge can result in more precise translations. Herein, "vous" would still correspond to "you", but its specification as "B?/?? OR tu > thou > ??" is achieved through appending.

As such, it is advised to utilize simple English language with enough context when writing. The inclusion of phrases like "you all" may enhance the quality of translation. Several languages do not possess a straightforward method for translating to or from English. In such instances, translations are done through a bridge language coupled with English. These languages comprise Belarusian (be - ru - en - other), Catalan (ca - es - en - other), Galician (gl - pt - en - other), Haitian Creole (ht-fr-en-other), Macedonian (mk-bg-en-other), Slovak(sk-cs-en-other), Ukrainian(uk-ru-en-other) and Urdu(ur-hi-en-other). Overlooking grammatical principles of specific languages can lead to errors. For instance, take this sentence: ?????(3rd person: it writes) ???(dative:to you(all)) ??????(letter) ?????(family) ?????(genitive:of Daria). Depending on word sequence, Google interprets this as:"You wrote a letter to family Darya." But when declensions(word roles) are considered,it translates into:"[It's]Daria's family [that] writes you a letter," implying the reverse meaning.Google misinterpreted "you" as "to you", "Daria" as "of Daria",and "the family" simply as “family.”

Google asserts that its translation of the text back into Russian is precise as ????? ????? ????? ??? ??????. This is because Google understands the sequence of words in English. Keeping this same sequence or choosing to write in English could bring advantages as demonstrated previously. Och suggests that to build a robust foundation for an efficient statistical

machine translation system for a new language pair, one needs access to a bilingual text corpus (or parallel collection) consisting of more than a million words and two monolingual corpora each containing over a billion words.

Google has made use of documents produced by the United Nations to amass a significant volume of language data. This information is then used to develop statistical models that facilitate translation between different languages. The UN releases its documents in all six official UN languages, thereby providing a large 6-language corpus. Furthermore, Google officials have proactively sourced bilingual data from researchers at national conferences held in Japan. The dialogue found in Chapter III explores the subject of Google Translate compared to Manual Translate, as was initially referred to in Chapter I.

This section will delve deeper into the subject, aiming to understand it from our viewpoint. Google Translate, a cost-free multilingual machine-translation service offered by Google Inc., converts text from one language to another. This tool is frequently employed in various fields such as education, engineering, healthcare, and civil services and is incredibly helpful when encountering challenges in comprehending an unfamiliar language. Despite its significant role in academia and particularly among learners for whom English isn't their primary language, this resource could potentially pose negative effects.

The potential risk of Google Translate in relation to a student's translation skills lies in its reliance on statistical matching rather than using dictionary definitions or grammar guidelines. Consequently, the translated content may consist of illogical mistakes and reversed sentence meanings. This presents an issue for English learners who require understanding of articles, books, and English literature.

The lack

of vocabulary mastery can become a hindrance for students. As a result, they often resort to using Google Translate as an alternative. However, this reliance on the tool leads to a decline in their translation abilities. Students become procrastinators and neglect manual translation efforts. They fail to recognize that using Google Translate results in errors, poor grammar, and subpar quality in their written text. Consequently, they become dependent on the tool and are unable to complete their writing or reading assignments. This situation is particularly detrimental for students working on their thesis.

What will happen to their thesis? It is unfortunate that our graduation has been diminished in terms of ability due to this simple thing. As English students, we have never attempted to do manual translation and improve our natural language acquisition skills through writing and reading (as speaking and listening are not directly affected by this phenomenon, so I am only mentioning the two of them). Moreover, if we observe other countries, they place great importance on this aspect because through these two abilities, students also enhance their critical thinking skills and develop strong writing proficiency.

The concept of Manual Translation, though labor-intensive and effortful, is becoming less popular. Despite its demanding nature, it holds substantial value. The impact of engaging in Manual Translation is not immediate but unfolds steadily throughout the process. Personally, my participation in this activity has significantly boosted my grasp on vocabulary and facilitated a smoother expression of my thoughts due to an expanded linguistic repertoire. This enhancement primarily stems from our zeal for reading various forms of text such as articles, books, literary works etc. CHAPTER

IV CONCLUSION The juxtaposition of Google Translate and Manual Translation offers a novel perspective that isn't frequently explored.

As part of the English Department, we are expected to possess superior language abilities, specifically in the educational sector since we aspire to be English educators. It's permissible to use resources such as Google Translate, but it's crucial to use them sparingly and focus more on human translation. This is because any effort dedicated towards manual translation is always beneficial. In time, innovative strategies may be introduced that enhance the experience of manual translation for international students, motivating them to invest their time and energy into it.