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How to Paraphrase | Step-by-Step Guide & Examples

How to Paraphrase | Step-by-Step Guide & Examples

Published on April 8, 2022 by Courtney Gahan and Jack Caulfield. Revised on June 1, 2023.

Paraphrasing means putting someone else’s ideas into your own words. Paraphrasing a source involves changing the wording while preserving the original meaning.

Paraphrasing is an alternative to quoting (copying someone’s exact words and putting them in quotation marks ). In academic writing, it’s usually better to integrate sources by paraphrasing instead of quoting. It shows that you have understood the source, reads more smoothly, and keeps your own voice front and center.

Every time you paraphrase, it’s important to cite the source . Also take care not to use wording that is too similar to the original. Otherwise, you could be at risk of committing plagiarism .

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How to paraphrase in five easy steps, how to paraphrase correctly, examples of paraphrasing, how to cite a paraphrase, paraphrasing vs. quoting, paraphrasing vs. summarizing, avoiding plagiarism when you paraphrase, other interesting articles, frequently asked questions about paraphrasing.

If you’re struggling to get to grips with the process of paraphrasing, check out our easy step-by-step guide in the video below.

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Putting an idea into your own words can be easier said than done. Let’s say you want to paraphrase the text below, about population decline in a particular species of sea snails.

Incorrect paraphrasing

You might make a first attempt to paraphrase it by swapping out a few words for synonyms .

Like other sea creatures inhabiting the vicinity of highly populated coasts, horse conchs have lost substantial territory to advancement and contamination , including preferred breeding grounds along mud flats and seagrass beds. Their Gulf home is also heating up due to global warming , which scientists think further puts pressure on the creatures , predicated upon the harmful effects extra warmth has on other large mollusks (Barnett, 2022).

This attempt at paraphrasing doesn’t change the sentence structure or order of information, only some of the word choices. And the synonyms chosen are poor:

“Advancement and contamination” doesn’t really convey the same meaning as “development and pollution.”
Sometimes the changes make the tone less academic: “home” for “habitat” and “sea creatures” for “marine animals.”
Adding phrases like “inhabiting the vicinity of” and “puts pressure on” makes the text needlessly long-winded.
Global warming is related to climate change, but they don’t mean exactly the same thing.

Because of this, the text reads awkwardly, is longer than it needs to be, and remains too close to the original phrasing. This means you risk being accused of plagiarism .

Correct paraphrasing

Let’s look at a more effective way of paraphrasing the same text.

Here, we’ve:

Only included the information that’s relevant to our argument (note that the paraphrase is shorter than the original)
Introduced the information with the signal phrase “Scientists believe that …”
Retained key terms like “development and pollution,” since changing them could alter the meaning
Structured sentences in our own way instead of copying the structure of the original
Started from a different point, presenting information in a different order

Because of this, we’re able to clearly convey the relevant information from the source without sticking too close to the original phrasing.

Explore the tabs below to see examples of paraphrasing in action.

Journal article
Newspaper article
Magazine article

Once you have your perfectly paraphrased text, you need to ensure you credit the original author. You’ll always paraphrase sources in the same way, but you’ll have to use a different type of in-text citation depending on what citation style you follow.

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It’s a good idea to paraphrase instead of quoting in most cases because:

Paraphrasing shows that you fully understand the meaning of a text
Your own voice remains dominant throughout your paper
Quotes reduce the readability of your text

But that doesn’t mean you should never quote. Quotes are appropriate when:

Giving a precise definition
Saying something about the author’s language or style (e.g., in a literary analysis paper)
Providing evidence in support of an argument
Critiquing or analyzing a specific claim

A paraphrase puts a specific passage into your own words. It’s typically a similar length to the original text, or slightly shorter.

When you boil a longer piece of writing down to the key points, so that the result is a lot shorter than the original, this is called summarizing .

Paraphrasing and quoting are important tools for presenting specific information from sources. But if the information you want to include is more general (e.g., the overarching argument of a whole article), summarizing is more appropriate.

When paraphrasing, you have to be careful to avoid accidental plagiarism .

This can happen if the paraphrase is too similar to the original quote, with phrases or whole sentences that are identical (and should therefore be in quotation marks). It can also happen if you fail to properly cite the source.

Paraphrasing tools are widely used by students, and can be especially useful for non-native speakers who may find academic writing particularly challenging. While these can be helpful for a bit of extra inspiration, use these tools sparingly, keeping academic integrity in mind.

To make sure you’ve properly paraphrased and cited all your sources, you could elect to run a plagiarism check before submitting your paper. And of course, always be sure to read your source material yourself and take the first stab at paraphrasing on your own.

If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.

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Plagiarism

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Common knowledge

To paraphrase effectively, don’t just take the original sentence and swap out some of the words for synonyms. Instead, try:

Reformulating the sentence (e.g., change active to passive , or start from a different point)
Combining information from multiple sentences into one
Leaving out information from the original that isn’t relevant to your point
Using synonyms where they don’t distort the meaning

The main point is to ensure you don’t just copy the structure of the original text, but instead reformulate the idea in your own words.

Paraphrasing without crediting the original author is a form of plagiarism , because you’re presenting someone else’s ideas as if they were your own.

However, paraphrasing is not plagiarism if you correctly cite the source . This means including an in-text citation and a full reference, formatted according to your required citation style .

As well as citing, make sure that any paraphrased text is completely rewritten in your own words.

Plagiarism means using someone else’s words or ideas and passing them off as your own. Paraphrasing means putting someone else’s ideas in your own words.

So when does paraphrasing count as plagiarism?

Paraphrasing is plagiarism if you don’t properly credit the original author.
Paraphrasing is plagiarism if your text is too close to the original wording (even if you cite the source). If you directly copy a sentence or phrase, you should quote it instead.
Paraphrasing is not plagiarism if you put the author’s ideas completely in your own words and properly cite the source .

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To present information from other sources in academic writing , it’s best to paraphrase in most cases. This shows that you’ve understood the ideas you’re discussing and incorporates them into your text smoothly.

It’s appropriate to quote when:

Changing the phrasing would distort the meaning of the original text
You want to discuss the author’s language choices (e.g., in literary analysis )
You’re presenting a precise definition
You’re looking in depth at a specific claim

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Gahan, C. & Caulfield, J. (2023, June 01). How to Paraphrase | Step-by-Step Guide & Examples. Scribbr. Retrieved April 9, 2024, from https://www.scribbr.com/working-with-sources/how-to-paraphrase/

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Translation Techniques – Paraphrasing

A paraphrase is a restatement of the meaning of a text or passage using other words. The term itself is derived via Latin paraphrasis from Greek, meaning “additional manner of expression”. In the past, paraphrasing and translation were considered to be unconnected language processing tasks.

Things have changed and now we can consider paraphrasing a translation technique due to its utility in improving the structure and the message of the text.

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If we compare translation and paraphrasing, we observe that the first one represents the preservation of meaning when an idea is rendered in the words in a different language, whereas the latter is the preservation of meaning when an idea is expressed using different words in the same language. It is obvious that the two processes are related.

If we analyse, we can actually define translation as the art of paraphrasing a text from one language into another. As there is always more than one way to phrase a statement, then the result in the target text depends on the translator’s choice. Finding alternative ways to translate a phrase can be a very useful tool for a translator.

First of all, it can have positive effects on the style of the written piece, secondly it can avoid repetition of certain words and structures that is often problematic and it can also help shorten the text when the space requires doing so.

A paraphrase usually gives an explanation or a clarification of the text that is being paraphrases. It can be a useful technique for the reader as well, as it helps him easily understand the meaning of a certain phrase.

Depending on the translator’s choice, a paraphrase can make the text sound more natural, more ambiguous or more formal. It is a matter of imposed style in this case. An example of paraphrasing is:

“The signal was red” = “The train was not allowed to pass because the signal was red”.

We can observe here that besides expressing the same thing in a different way, paraphrasing actually gives an explanation. A paraphrase does not need to accompany a direct quotation; the paraphrase typically serves to put the source’s statement into perspective or to clarify the context in which it appeared. A paraphrase is typically more detailed than a summary. Paraphrasing usually aims at preserving the essential meaning of the material that is being translated and paraphrased. It means that the reinterpretation of a source that gives a different meaning to the original statement goes into the category of original research and not paraphrase.

The difference between a metaphrase and a paraphrase is that the first attempts to translate a text literally, whereas a paraphrase conveys the essential thought expressed in a source text even at the expense of literality. To conclude, paraphrasing can be considered a translation technique. It is proved that it is a useful tool for translators and writers and it helps improve the quality of the text. The reader benefits from this technique as well because it often clarifies the meaning of the text.

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Original article
Open access
Published: 19 December 2018

Paraphrasing tools, language translation tools and plagiarism: an exploratory study

Felicity M. Prentice ORCID: orcid.org/0000-0003-4962-7413 1 &
Clare E. Kinden 1

International Journal for Educational Integrity volume 14 , Article number: 11 ( 2018 ) Cite this article

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In a recent unit of study in an undergraduate Health Sciences pathway course, we identified a set of essays which exhibited similarity of content but demonstrated the use of bizarre and unidiomatic language. One of the distinct features of the essays was the inclusion of unusual synonyms in place of expected standard medical terminology.

We suspected the use of online paraphrasing tools, but were also interested in investigating the possibility of the use of online language translation tools. In order to test the outputs of these tools, we used as a seed document a corpus of text which had been provided to the students as prompt for the essay. This document was put through six free online paraphrasing tools and six separate iterative language translations through the online Google Translate™ tool.

The results demonstrated that free online paraphrasing tools did not identify medical terminology as standardised or accepted nomenclature and substituted synonyms, whereas Google Translate™ largely preserved medical terminology.

We believe that textual indicators such as the absence of standard discipline-based terminology may be of assistance in the identification of machine paraphrased text.

Introduction

Imagine you are reading a student’s essay and are confronted with the following sentence:

A situation that can give resistance and additionally generally safe for botches, and that inspects choices without assaulting the pride and nobility of the individual influencing them, to will prompt better natural decisions.

In an assessment task set for first year undergraduate Health Science students in a pathway program, an alarming proportion of submitted work, nearly 10%, demonstrated linguistic contortions similar to the example given. This led us to consider the following questions:

Were students using online paraphrasing tools to manipulate work which was written in English and which had not been authored by them?

Were students who had English as an Additional Language (EAL) composing work in their first language and then translating this through online language translation tools?

Are there indicators which can identify the use of on-line paraphrasing tools?

All examples of unusual writing provided in this article are indicative of the nature of the student writing encountered but have been altered to retain anonymity while preserving the features of the linguistic anomalies.

While standards of English expression may vary considerably in work submitted by students, it is becoming more common to encounter essays which display standards of writing well below that which is expected of students studying in Higher Education. When the student is from an English as an Additional Language (EAL) background, poor expression in written work has been attributed to lack of facility with the language, clumsy patchwriting, or the use of an online translation tool, such as Google Translate™ (n.d.) ( https://translate.google.com.au ). Mundt and Groves ( 2016 ) contend that when students use an online translation tool to convert their own work from their first language into English this may be considered demonstrative of poor academic practice, as they are not actively developing English language skills. However, as the original work is the result of the student’s own intellectual merit, it is contentious as to whether this qualifies as academic misconduct. In the case of the submissions we received there was reasonable suspicion that the text had not been subject to a language translation tool but had been reengineered by an English-to-English paraphrasing tool. This called into question the source of the original English text, and suggested there was evidence of a genuine breach of academic integrity.

Rogerson and McCarthy ( 2017 ) reported that their initial awareness of paraphrasing tools was through a casual comment by a student. In our case, the serendipitous discovery of online paraphrasing tools was made when one of the authors was following an online forum discussing cheating methods. Prior to this revelation, our assumptions as to the origin of incomprehensible student writing had been more naïve, our explanations being focussed around patchwriting and LOTE-to-English translation tools. However, when encountering the extent of the use of inappropriate synonyms in essays submitted for this particular assessment task, we were moved to examine the text more closely. A review of one or two essays rapidly escalated to the identification of a cluster of essays which bore remarkable similarity in the use of peculiar language, and in particular the inclusion of bizarre synonyms for standard recognised terminology within the health sciences discipline. Further to this, there was significant similarity in the structure of the essays, where the information, and even in-text citations, were provided in an identical sequence. In some cases, the Turnitin® (n.d.) similarity index identified a match between a number of essays, but other suspicious works resulted in an index of 0%. It became clear that paraphrasing tools were probably being used and that students were colluding to paraphrase each other’s essays.

The literature is replete with the lamentations of academics who feel that pursuing academic misconduct forces them in to the role of detective. Collecting evidence, analysing scenarios, motives and prior offences and operating in a quasi-judicial, if not criminological paradigm, does not sit well within the cultural norms of academia (Brimble and Stevenson-Clarke 2006 ; Burke and Sanney 2018 ; Coren 2011 ; Keith-Spiegel et al. 1998 ; Sutherland-Smith 2005 : Thomas and De Bruin 2012 ). Our experiences seemed to resonate so clearly with this sentiment to the point where we felt a profound urge to recreate a television crime show, with essays taped to the wall connected by string, surrounded by tacked-up maps and photographs of the suspects.

The breakthrough came when an essay was so alarmingly absurd that we were able to trace the origin to another student’s essay. The assessment task was to analyse and discuss a scenario regarding a young Indigenous man’s experiences in the Australian Health Care System.

One student included in their essay a description of a Computerised Axial Tomography (CAT) scan which had been plagiarised from a Wikipedia page. However, in transcribing how images were taken from various angles, they had misspelled the word ‘angles’ as ‘angels’. This spelling error had not caused concern, however work submitted by another student provided evidence that there was a curious literary connection between the essays. In this case the second student reported that the CAT Scan images were taken from various ‘Blessed Messengers’.

It was apparent that the second student had used a paraphrasing tool to ‘spin’, that is, to apply synonym substitution, to the essay obtained from their colleague.

Given the poor standard of the output, why would a student resort to using paraphrasing tools? Paraphrasing is a complex and demanding task, requiring students to demonstrate not only understanding of the meaning and purpose of the text, but also to find the linguistic facility to restate this meaning in new and original words, and specifically in the discourse of Academic English (Shi 2006 ).This task is difficult enough when performed in a first language, and the challenge is magnified when the student is from a non-English speaking background (Bretag 2007 ; Carroll 2015 ; Correa 2011 ; Handa and Power 2005 ; Marshall and Garry 2006 ).

Bretag ( 2007 ) describes two aspects of the acquisition of a second language. Basic interpersonal communication skills can be developed in approximately two years, however it is estimated to take five to ten years to develop cognitive academic linguistic proficiency which is necessary to function in an academic learning environment. Patchwriting is when students attempt to paraphrase a source by substituting synonyms in passages while retaining too closely the voice of the original writer (Jamieson 2015 ). This may be classified as an intermediary stage of the development of academic linguistic proficiency representing a form of non-prototypical plagiarism (Pecorari 2003 ). As such, it may not be a deliberate or intentional breach of academic conduct. In students with EAL, the acquisition of the linguistic facility to represent the meaning of a text without resorting to reproducing the author’s actual words may take more than the few months that our students have been studying at an English-speaking University. However, in the cases under consideration, students did not attempt to manually re-engineer text in order to paraphrase but used an online paraphrasing tool to alter the entire corpus of the text. The original source text could be identified in many cases by a recognition of some structural features, for example, the reproduction of the scenario provided to the students.

Original One day, while Doug was out walking, he felt lightheaded and then lost consciousness and fell to the ground. He was brought to the Emergency Department of a major hospital by ambulance for assessment and investigation.

Post paraphrasing tool While one day on his walk Doug he felt bleary eyed and lost awareness and fell onto the ground. He was conveyed to the Emergency Department of the healing facility for significant appraisals and tests.

In some cases the original source was taken from the internet, notably Wikipedia, but in one instance the student lifted and paraphrased text taken directly from a file sharing site. The student did not provide an in-text citation, however the original source was identified by the student including the file sharing website address in the reference list. This has been referred to as illicit paraphrasing (Curtis and Vardanega 2016 ), and actions such as this may call into question the level of intentionality to deceive. The inclusion of a reference, albeit from an inappropriate source, may suggest the student was attempting to participate in the expectations of academic practice. Less generously, it may be assumed that copying material directly from a file sharing site, using a paraphrasing tool to deceive Turnitin® (n.d.) , and then submitting the work, even with a hopeful inclusion in the reference list, demonstrated an intentional breach of academic integrity.

Patchwriting

Strategic word substitution has always been a feature of students’ attempts at paraphrasing, which Howard defined as patchwriting,

Copying from a source text and then deleting some words, altering grammatical structures, or plugging in one synonym for another. (Howard 1999 , p.xvii, in Jamieson 2015 )

While patchwriting by students has been characterised as poor academic practice, it is also seen as a preliminary effort to become familiar with the discourse of academic writing (Pecorari 2003 ).

In the essays considered in this exploratory study, we encountered examples of English expression which indicated that the EAL student was struggling to develop fluency, for example:

Doug leaves his home and move far away from his family to the city. There he have house with an unknown people and he have feeling of loneliness and unhappy. He is not able to get the job and had very small income. He was usually sad and feel bad in himself. It is all these factors lead to a poor health.

We were also able to recognise patchwriting in text that had been appropriated from multiple sources, and these incidents were usually identified by Turnitin® (n.d.) and exemplified by a ‘rainbow’ of colours in the similarity report demonstrating different sources. However, in the essays under investigation the text demonstrated the inclusion of synonyms resulting in writing which was largely unintelligible. Further to this, there had been no manipulation of the syntax of the sentences, which heightened the unidiomatic nature of the writing. Whereas in patchwriting synonyms are manually substituted by the student, online paraphrasing tools achieve this through an automatic function, and thus the question arises, as posited by Rogerson and McCarthy ( 2017 ), as to whether the use of online paraphrasing tools transcends patchwriting to become what Walker describes as illicit paraphrasing (in Pecorari 2003 , p.9).

Expected medical terminology

One of the most obvious issues we encountered in the essays was the use of synonyms for standard medical terminology. Standardised nomenclature and terminology are employed throughout health care to avoid ambiguity in documentation and communication. This provides the interface for meaningful and appropriate communication of medical, nursing and allied health information regarding patient care, and is an essential element of safety and standardisation in care (Pearson and Aromataris 2009 ). In addition, this terminology is used for medical information classification, and has been raised as a priority area in the introduction of electronic health records to ensure interoperability across systems and health disciplines (Monsen et al. 2010 ). The importance of employing correct and predictable terminology has been identified as paramount in avoiding adverse outcomes:

Current research indicates that ineffective communication among health care professionals is one of the leading causes of medical errors and patient harm. (Dingley et al. 2008 , p.1)

Therefore, the acquisition and correct contextual application of medical terminology is a fundamental part of learning in health sciences. Students are exposed to this terminology throughout their studies, and in the case of the assessment task under scrutiny, students were provided a scenario, or enquiry prompt, which included the standard discipline-based terminology (see Appendix ). The lack of standard medical terminology and the inclusion of unusual synonyms for this terminology was a significant feature of the essays. In the event that students were exhibiting difficulties with English expression, or were manually substituting synonyms as seen in patchwriting, it would be expected that the standard terminology would be preserved. This led us to suspect, and subsequently investigate, online paraphrasing tools.

Paraphrasing tools

Spinning is a technique used to produce a new document, or documents, from an original text source by replacing words in such a way as to retain the overall meaning of the text, while avoiding machine-based text matching tools used to identify plagiarism. Machine based paraphrasing tools were developed to enable text spinning as a way of improving website rankings in Google search results and are part of a suite of search engine optimisation (SEO) techniques referred to as Black-Hat marketing. (Lancaster and Clarke 2009 ; Rogerson and McCarthy 2017 ; Zhang et al. 2014 ).

In web-based marketing the goal is to get the highest ranked place in a Google search index.

The Google search engine identifies and calculates the frequency of links between, and website traffic to, each website and ranks sites on the search results accordingly. In Black Hat marketing, the aim is to create sites including blogs, articles and webpages which provide multiple links to the target page, thus ensuring optimisation of the search engine results and a higher overall ranking (Bailey 2018 ).

Google search engines use word matching software which can recognise duplicate text and penalties are applied where this has been detected, hence the need to create paraphrasing tools which will instantly produce duplicate text material which cannot be detected. These paraphrasing tools were designed to hoodwink word matching software but were not intended to emulate human generated text. It is apparent that students are now using these tools to spin text from numerous original sources with the aim to deceive word matching software such as Turnitin® (n.d.) .

The free online automated paraphrasing tools rely principally on synonym substitution without altering the overall syntax of the sentence, resulting in language which is unidiomatic at best, incomprehensible at worst.

When Rogerson & McCarthy published in 2017, they reported that a simple Google search for paraphrasing tools resulted in over 550,000 hits. Our search in 2018 demonstrated a proliferation of paraphrasing sites resulting in over 3,320,000 hits. Cursory examination revealed that many are duplicate sites with the same tool offered under different names. Of greater concern is the increased juxtaposition of advertisements and links to essay purchasing services. Anticipating the vulnerability of the student, some sites offer a free paraphrasing tool but ensure the output is extremely poor.

For example, when the following sentence taken from the assessment scenario:

One day, while Doug was out walking, he felt lightheaded and then lost consciousness and fell to the ground. He was brought to the Emergency Department of a major hospital by ambulance for assessment and investigation.

is entered into a free online paraphrasing tool the following results were obtained:

Brace girl, stretch Doug was at large peripatetic, he felt lightheaded and fit lost consciousness and fell to the ground. He was debasement to the Danger Diversify of a chief sanatorium by ambulance for weight and criticism. Plagiarisma http://plagiarisma.net/spinner.php

One sidereal day, while Doug was out walk, he felt lightheaded and then lost knowingness and downslope to the pulverization. He was brought to the Emergency Department of a major hospital by ambulance for assessment and probe. Rephraser https://www.rephraser.net/instant-paraphrasing-tool/

This word salad is used to entice students into contract cheating, that is, outsourcing the assessment task to be completed by a third party (Lancaster and Clarke 2006 ). The sites provide a link to an essay writing service, in one case with a curiously poorly worded advertisement stating:

Aren’t satisfied with the results? But what to expect from the tool? Hire an expert for a quality rewording! Only $8.39/page. Paraphrasing Online https://www.paraphrasingonline.com

Paraphrasing tools work by creating an intermediate text referred to as “spintax”, where a number of synonyms are provided for each selected word, for example the phrase:

the junior doctor in the rehabilitation centre prepared a discharge summary

is transformed into the intermediary spintax:

the {understudy specialist | lesser specialist | lesser pro} in the {recovery fixate | recovery focus | rebuilding centre} prepared a {release rundown | release report | blueprint}.

Based on a number of parameters, words can be substituted at varying rates within a sentence, however it is non-deterministic. Therefore, for the purpose of Black Hat marketing, this provides a vast number of permutations for the creation of articles which are sufficiently different from each other to evade detection by word matching software (Bailey 2018 ). This explains why students using paraphrasing tools may generate apparently different essays from a single seed document.

To create the spintax, a bank of potentially alternative terms is held in a synonym dictionary, which may be local to the paraphrasing tool, or held in cloud storage (Shahid et al. 2017 ; Zhang et al. 2014 ). In their study, Zhang et al. ( 2014 ) were able to access this dictionary and reverse engineer two paraphrasing tools (Plagiarisma and The Best Spinner) to establish which words are subject to synonym substitution, referred to as ‘mutables’ , and which words do not appear in the synonym dictionary and thus would not be included in the spintax, referred to as ‘immutables’ . This approach, referred to as DSpin, relies on comparing the unchanged text, or immutables, located within the spun text to the original text (Zhang et al. 2014 ). The match of immutable terms between documents (spun and original) will provide evidence of the source of the text. We became interested in the concept of immutable words and how these may be used to identify documents that had been machine paraphrased.

The paraphrasing tools that require a fee-based subscription provide a large number of parameters to manipulate the output, including the contents of the dictionary, the maximum number of synonyms used and replacement frequency, and the replacement of both single words and short phrases (Shahid et al. 2017 ). In this study we assumed that the students were accessing the fee free version of online paraphrasing tools and as a result the output of spinning was less subject to control resulting in more words treated as mutables and thus less discretionary synonym substitution.

As medical terminology is fundamental to the discourse of health sciences, it would be reasonable to classify these words as preferentially immutable . However, the paraphrasing tools do not have the capacity to recognise the significance and importance of these terms, and thus they are within the synonym dictionary as mutables and subject to synonym substitution.

Students in this unit of study are exposed to medical terminology throughout the curriculum, and it is emphasised that these terms are fundamental to the discourse and required for communication in health sciences. Hyland ( 2006 ) notes that becoming a member of a discourse community involves “learning to use language in disciplinary approved ways” (p.38). They are expected to use these terms, and it is clear in the rubric and marking guides that the assessment is aligned to the objective of the acquisition of this specialised language. The scenario provided in this assessment was rich and replete with the terminology, and there was ample opportunity for imitation and reproduction of the writing style and nomenclature. Therefore, the absence of the recognised terminology and the inclusion of unidiomatic and contextually invalid synonyms was particularly obvious to the readers.

Method of analysis

Identifying the use of paraphrasing tools.

It could be argued that the use of synonyms, in particular archaic or unidiomatic words and phrases, is a clear indicator that machine generated paraphrasing has been used. For example, in the papers submitted by students where the use of paraphrasing tools was suspected, the term aboriginal man was substituted with autochthonic person , the hospital became the mending office , the rehabilitation centre the recovery fixate , and the discharge summary the release precis .

In order to investigate the extent to which paraphrasing tools substituted recognised and expected medical terms for unusual synonyms, we selected three essays which we had identified as particularly unusual. We did not know the provenance of these essays, although there was structural evidence that they might have arisen from a single seed document which was an essay submitted by one student in the current cohort.

Table 1 shows the variation from the expected nomenclature.

Comparing online language translation and paraphrasing tools

Prior to learning of the existence of online paraphrasing tools, we had assumed that students were authoring work in their first language, and then using online translation tools to convert the text to English. Perhaps the most notable and available online free translation tool, Google Translate™, was made available as an online tool in 2006 using a statistical machine translation engine to translate text from one language, via English, on to the target language. In 2016 Google implemented a Neural Machine Translation engine, which has provided a more sophisticated and accurate output (Le and Schuster 2016 ). Given the idiomatic nature of language, errors may still occur where a word is translated into a synonym which may not be contextually valid.

To investigate the possibility that students had used Google Translate™, the scenario provided as the enquiry-based learning prompt was used as a seed document to ascertain the changes which might occur when paraphrasing tools and Google Translate™ were employed. The scenario ( Appendix ) was put through a number of paraphrasing tools, and in each case the standard medical terminology was consistently changed. When the scenario was put through Google Translate™, the terminology was changed only rarely.

The scenario document was subject to iterative language translation (Day et al. 2016 ). The text was entered into Google Translate™ for translation to a language other than English, and this translation was copied and re-entered to a refreshed Google Translate™ page for translation back into English. The target languages used were Arabic, Punjabi, Hindi, Chinese (Simplified), Chinese (Traditional) and Vietnamese. The languages were chosen as they represent the principal first languages of the EAL students enrolled in this subject.

The translations were of a generally good quality, displaying minor errors in tense and pronoun gender, but could be easily comprehended. The most accurate translations were Chinese (Simplified and Traditional) and Vietnamese, and the highest number of errors occurred in Arabic, Hindi and Punjabi. In the latter languages there were more substitutions for standardised health terms (Table 2 ).

The original scenario was then put through six paraphrasing tools selected as the top entries generated by a Google search using the term ‘paraphrasing tools’ . This technique follows that used by Rogerson and McCarthy ( 2017 ) based on the assumption that students would use a similar search strategy and select the sites listed at the top of the search results (Table 3 ).

It was not known whether these sites were using the same paraphrasing tool, however, given the multiple outputs available through non-discriminatory synonym substitution, there was ample opportunity for a diverse output.

The results from the output texts were analysed for synonym substitution of recognised and expected medical terminology, and this was compared to the outputs from the iterative language translation through Google Translate™. This technique was used for convenience purposes as the intention was to gain an overall impression of the extent to which medical terms were substituted by paraphrasing tools compared to Google Translate™. As can be seen from Table 4 , the proportion of substituted terms was significantly different. From the 21 standard medical terms there were 73 synonyms from the paraphrasing tools and 7 alternative terms from Google Translate™. Blank spaces in the table indicate that no alterative term was generated by Google Translate™.

Although it is not within the scope of this brief exploratory study to state that there is a measurable difference in synonym substitution between paraphrasing tools and Google Translate™, the above results give a general indication of the observable differences.

When determining whether there is a potential breach in academic integrity, it is important to distinguish between extremely poor English skills, the use of a LOTE-to-English translation device, and the generation of text through a paraphrasing tool. Carter and Inkpen ( 2012 , p.49) note “Machine translated text often seems to be intuitively identifiable by proficient speakers of a language”. If a student has used paraphrasing tools to alter a text to evade detection of plagiarism, then that act of evasion suggests that plagiarism has occurred. Word matching software such as Turnitin® (n.d.) has proven valuable in identifying replication of text from other sources. However, the very purpose of paraphrasing tools is to deceive software developed to detect plagiarism, and it is apparent that to date this strategy has been successful (Lancaster and Clarke 2009 ; Rogerson and McCarthy 2017 ; Shahid et al. 2017 ). Consequently, the burden of detection remains with the human reader who has to become increasing adept at spotting stylistic variations and any other flags relating to mechanisms that have been used to avoid detection (Gillam et al. 2010 ).

The method of detection we suggest, identifying the absence of expected nomenclature such as discipline based terminology, could be considered an extrinsic analysis of the text. The expected immutables of recognised medical terms are substituted with synonyms, and thus treated by the paraphrasing tools as mutables . The paraphrased text is compared to an ideal or external text, that is, the text containing the medical terminology which was expected by the assessor. Shahid et al. ( 2017 ) propose a method of intrinsic analysis of paraphrased text through stylometric analysis:

We observe that style, language, grammatical constructs, and certain linguistic expressions in spun documents deviate from a human author because spinning software introduce artefacts in their output which are specific to a text spinner. (p. 5)

The technique described in their study involves the application of a number of algorithms to a selected text which can lead to identification of the source text. This level of analysis is not currently available to academic staff seeking to identify plagiarism committed through the use of paraphrasing tools. However, Turnitin® (n.d.) is developing an Authorship Investigation tool which will use stylometric and forensic linguistic analysis to provide measurement parameters indicative of authorship of a text ( https://www.turnitin.com/solutions/authorship-investigation ,). Where there is suspicion that contract cheating has occurred, the Authorship Investigation tool will use examples of previous work submitted by a student to ascertain similarity of stylistic features to the work under suspicion. The premise is that a stylometric ‘fingerprint’ of the student’s literary style and expression can be used for comparison to submissions which may have been outsourced to another author. It is anticipated that this tool will be of potentially useful in determining whether a submission has hallmarks which distinguish it from other pieces of writing by the student, but it will not be possible to identify the author of the outsourced work.

In this exploratory study we identified linguistic features of spun text which indicated the use of paraphrasing tools. However, we were reliant on the curious case of the blessed messengers to point towards collusion. This was achieved through close collaboration by the marking staff, and until techniques for reverse engineering of paraphrased text become more widely available, “What ultimately leads to determinations of plagiarism is considerable manual analysis and subjective judgement” (Bretag and Mahmud 2009 , p.54).

Students, and in particular those from an EAL background, experience significant challenges in conforming to academic conventions such as paraphrasing. The availability of free online paraphrasing tools may appear to them as a realistic solution to these challenges despite the word salad which is created by these tools. Whereas EAL students who write original work in their first language and then use online translation tools to convert this to English may be demonstrating poor academic practice, it can be argued that the submitted work is a result of their own intellectual endeavours. Unfortunately, students who use paraphrasing tools to spin text from undisclosed sources, thus evading word matching software, have committed an overt act of academic dishonesty.

In academic writing in the health science discipline, there is an expectation that standard medical terminology will be used. We noted that absence of this in the students’ submissions and investigated the outputs of both paraphrasing tools and Google Translate™. We noted that paraphrasing tools are significantly more likely to substitute inappropriate synonyms for accepted medical nomenclature, whereas Google Translate™ largely preserved these terms intact.

When paraphrasing tools have been applied to text the output is frequently of such poor quality as to render the text unintelligible. We also noted the following features: the language generated will be notable for the use of unidiomatic words and phrases; expected vocabulary such as standard medical terminology will usually be substituted with inappropriate synonyms; word matching software, such as Turnitin® (n.d.) , may not recognise the re-engineered text from the source and thus provide a low similarity index which may not be indicative of the actual level of plagiarism.

When using online translation tools, such as Google Translate™, to convert text from a language other than English to English, there is less likelihood that discipline specific nomenclature, such as standard medical terminology, will be changed to the same extent as paraphrasing tools.

This study demonstrates that there are a number of distinct features which can be identified in the text generated by paraphrasing tools. Awareness of these features will assist in the process of detecting plagiarism. While the emphasis should be on supporting students to develop the skills required to paraphrase appropriately, identifying linguistic markers which provide evidence of the use of paraphrasing tools will be of benefit in the overall management of breaches of academic integrity.

Abbreviations

Computerised Axial Tomography Scan

English as an Additional Language

Emergency Department

Language other than English

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Scenario for assessment task

Doug is a nineteen year old aboriginal man who has had Type I Diabetes Mellitus since he was 13. Doug was born in a small town in a remote area of Victoria. Despite not completing Year 8, he decided to move away from his family to the city. He has not been able to get a job and has very little income. He misses his family, friends and community, but is determined that they not find out that he is unhappy. Doug has a history of homelessness but has been living for the past 2 weeks in a share house with people he doesn’t know well. Doug does not see the same doctor for his diabetes , he visits many different clinics , depending on where he is living at the time.

As a consequence of the fall, he sustained a head injury which resulted in severe and persistent headaches, loss of coordination and difficulty with walking. In the Emergency Department (ED) a number of tests were undertaken (including a CAT scan , blood sugar test and full examination). It was identified that prior to the fall he had experienced an episode of ‘ insulin shock ’.

Following an 8 h stay in the Emergency department , Doug was transferred to the Neurology ward for assessment and monitoring. In addition to the medical records available in the central electronic filing system, a member of the ED team provided a ‘ handover ’ to the Nurse Unit Manager of the Neurology Ward .

It was when he was on this ward that the nursing staff identified that Doug has limited knowledge of his diabetes including where to access support and advice, and how to monitor his glucose levels and adjust his insulin dose properly. A team consisting of nurses , the ward physiotherapist , a social worker , and a neurologist met on three occasions to discuss Doug’s case. They used the information from the Emergency Department admission , the assessments undertaken by the team of health professionals , and included Doug in all their decisions. They identified his issue with Diabetes management, but as this was a short admission to the Neurology Ward , they did not have the resources to follow this up. After a 4 day stay in the Neurology ward , the healthcare team decided that Doug would benefit from being transferred to a rehabilitation centre . A junior doctor who had just joined the ward was given the task of writing the discharge summary .

Doug was taken by patient transport to a rehabilitation centre which was not part of the acute hospital , but an independently run organisation. The brief discharge summary was sent with Doug describing the initial head injury and noting the need for ongoing therapy to assist his co-ordination and walking. While in the rehabilitation centre , Doug was assessed by the physiotherapist , occupational therapist , doctor , and of course the nursing staff who monitored Doug daily. They did not seek any additional information from the acute hospital , only using the discharge summary as a basis for Doug’s care. They did not formally meet, but they each wrote notes in Doug’s medical record .

On day six of his admission to the rehab centre , the Nurse Unit Manager observed Doug confidently walking in the ward corridor by himself. As a very experienced Rehab Nurse she decided that Doug could be discharged home based on his ability to independently toilet and ambulate. In addition, she was under considerable pressure by the senior management of the Rehab Centre to discharge patients to free up beds. Without consulting the other staff, the Nurse Unit Manager informed Doug that he was to be discharged the following day as he now appeared fine and had no consequences from his “little bump on the head.”

Doug was discharged the next day and returned to the house he was sharing. None of his housemates had even realised he had been away. Five days following his discharge home, Doug was again admitted to the ED by ambulance, having suffered a fall at home while trying to descend the stairs from the second floor where his bedroom was located. He fractured his left tibia as a result of the fall. He told the ED staff that he had not been eating well, but that he had still injected his usual insulin dose just prior to the fall.

(Bold and italics provided by authors to highlight standard medical terminology).

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Prentice, F.M., Kinden, C.E. Paraphrasing tools, language translation tools and plagiarism: an exploratory study. Int J Educ Integr 14 , 11 (2018). https://doi.org/10.1007/s40979-018-0036-7

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If you need more summaries or simplifiying capacity, upgrade to one of our subscription plans

The Meaning of Meaning: A Study of the Influence of Language upon Thought and of the Science of Symbolism (1923)

This work has been used as a textbook in many fields including linguistics, philosophy, language, cognitive science and most recently semantics and semiotics in general. The chief idea probably is that Words and Things are connected “through their occurrence together with things, their linkage with them in a ‘context’ that Symbols come to play that important part in our life [even] the source of all our power over the external world”.

In this context system, the authors develop a 3-part semiotics—symbol, thought and referent with three relations between them. Symbols are then "those signs which men use to communicate one with another and as instruments of thought, occupy a peculiar place... All discursive symbolization involves... weaving together of contexts into higher contexts... So, for a word to be understood requires that it form a context with further experiences”...

(available during US EST office hours, but you can try anytime...)

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You can always do advanced rewrite for your texts from here !

Welcome to Formal Converter - Your All-in-One Tool for Formal Writing

Are you struggling to convert your informal writing into a more professional and formal tone? Look no further than Formal Converter - the ultimate tool for transforming your language quickly and easily. With range of services, including an informal to formal converter, formal writing generator, and more, you'll be able to write with confidence and impress your audience.

Transform Your Informal Language into Formal Language with a Informal to Formal Converter

Our free informal to formal converter makes it simple to convert casual and colloquial language into more sophisticated and professional language. No more worrying about sounding unprofessional - this tool will provide you with high-quality language that's suitable for any formal occasion.

Create Effective Sentences with a Formal Writing Generator

Our formal writing generator is an excellent resource for anyone who needs to write in a formal style. The tool provides you with sentence templates and ideas for formal writing, so you don't have to struggle with writing in a formal tone. Whether you're writing an academic paper, a business letter, or any other formal document, this generator will help you create effective sentences that make an impact.

Convert Your Existing Text with a Formal Text Converter

If you're struggling to write in a formal style, a formal text converter is here to help. The tool analyses your text and replaces casual language with formal language, making it easier for you to write in a professional tone. With this converter, you can transform your existing text into language that's suitable for any formal occasion.

Transform Formal Language into Informal Language with a Formal to Informal Converter

Our formal to informal converter is perfect for anyone who needs to convert complex language into a more conversational tone. Whether you're writing for social media, emails, or any other informal communication, this tool will help you convert your language with ease.

Create Professional Emails with a Formal Email Converter

If you want to create a lasting impression with your emails, this formal email converter is a must-have tool. The tool analyses your email and suggests changes to make it more formal and professional. With an email converter, you can avoid common mistakes and ensure that your emails are taken seriously.

Write Effective Sentences with a Formal Sentence Converter

Our formal sentence converter is an excellent resource for anyone who struggles with writing formal sentences. A tool provides you with different sentence structures that are suitable for formal writing, making it easier for you to create effective and professional sentences.

Transform Your English with a English to Formal English Converter

If English isn't your first language, writing in a formal tone can be challenging. That's why we offer an English to formal English converter that analyses your text and suggests changes to make it more formal and grammatically correct. With an English to formal English converter, you can write with confidence and avoid common mistakes.

Create a Lasting Impression with a Formal Letter Converter

Our formal letter converter is an excellent resource for anyone who needs to write a formal letter. The tool analyses your text and suggests changes to make it more professional and effective. With a formal letter converter, you can write letters that make a lasting impression.

Write Professional Language with a Formal Language Converter

Our formal language converter is designed to help you write in a more professional tone. The tool analyses your text and replaces casual language with formal language, making it easier for you to create effective and professional writing.

Start Writing with Confidence Today

In conclusion, Formal Converter is the ultimate tool for anyone who wants to write in a more professional and formal style. With a range of services, you'll be able to transform your language quickly and easily. So what are you waiting for? Start using Formal Converter today and take your writing to the next level.

Quick FAQ on converting informal & formal texts

Q: how can informal language be converted to formal language.

A: Use a formal language converter tool or manually use professional vocabulary and avoid slang and contractions.

Q: What are the differences between formal and informal language translation?

A: Formal language translation is more complex and technical, while informal language translation requires more creativity and interpretation.

Q: How do you transform a sentence from formal to informal/casual?

A: Use contractions, slang, and casual language, while keeping the context and audience in mind.

Q: What is the distinction between informal and formal language?

A: Formal language is professional and academic, while informal language is more casual and conversational.

Q: What are some tips for making text more formal?

A: Use professional vocabulary, avoid slang and contractions, follow grammar rules, use complex sentence structures, and adjust tone and formality based on audience and context.

How does an online informal to formal converter work?

An online informal to formal converter is an AI-powered tool that rephrases casual or colloquial language into a more professional or academic style. The tool analyzes the input text for informal expressions, slang, and contractions, and replaces them with their formal equivalents. Users simply input their informal text, and the AI uses natural language processing to output a formalized version.

Formal Converter Blog

How to convert informal text to formal text online.

Check out various online platforms and tools specifically designed to convert informal text into a more formal style, ensuring clarity and professionalism in your written communication.

Best tools for making emails more formal & professional

Here's a list of some of the best tools to help you craft polished, professional, and formal emails.

Differences between informal and formal writing styles

Check the nuances and distinctions between informal and formal writing styles to better understand their appropriate applications.

All new posts

About the informal to formal rewriter, can a formal to casual converter maintain the original message's intent.

Yes, a formal to casual converter is designed to maintain the original message's intent while transforming the tone to be more relaxed and conversational. The AI assesses the context of the formal text and applies casual language constructs, such as contractions and colloquialisms, without altering the underlying message.

Is using an AI converter for formal to casual language reliable?

Using an AI converter to transform formal language to casual language is generally reliable, as it employs sophisticated algorithms to understand and mimic human speech patterns. However, the accuracy can depend on the complexity of the text and the nuances of the language, so it's recommended to review the output for any subtle context or tone that may require manual tweaking.

What are the benefits of using an online converter for language styles?

Using an online converter for changing language styles saves time and ensures consistency throughout the text. It's particularly useful for non-native speakers or individuals who are not as familiar with the nuances between formal and casual language. Additionally, it's a valuable tool for learning and understanding the differences in language registers.

How can I trust the quality of an AI-generated formal text?

The quality of AI-generated formal text has improved significantly with advancements in natural language processing and machine learning. Many converters are trained on extensive corpora of professional and academic texts, enabling them to produce high-quality formal writing. Nevertheless, it's advisable to review the output, especially for important documents, to ensure it meets your standards.

Are there any limitations to using a formal to casual converter?

While formal to casual converters are powerful, they do have limitations. They might not always capture the subtleties of conversational tone or regional slang, and they may miss humor or idiomatic expressions. For texts that rely heavily on these elements, manual editing might still be necessary after conversion.

How does a formal to casual converter handle idioms and slang?

A formal to casual converter uses a database of idioms and slang to replace more formal phrases with their casual counterparts. However, the replacement depends on the AI's database and algorithms, so it may not always choose the most current or appropriate colloquial terms for all audiences.

What kind of texts are suitable for conversion with an informal to formal converter?

An informal to formal converter is ideal for texts that require a professional tone, such as business correspondence, academic papers, or official documents. It is also suitable for refining social media posts or emails when a more polished presentation is desired.

Can I customize the level of formality when using a converter?

Some advanced informal to formal converters may offer customization options, allowing users to select the desired level of formality. This feature helps to tailor the output to suit different contexts, whether for a corporate report or an academic article, ensuring appropriate language use.

How does an AI determine the correct formal equivalents in a conversion?

AI converters use natural language processing algorithms to understand the context and semantics of the text. They match informal expressions with formal equivalents based on language rules, patterns learned from formal text datasets, and sometimes user settings or preferences, to ensure the conversion makes sense within the given context.

Oracle Cloud Infrastructure Documentation

Document translation.

The document translation model translates text into a chosen language

OCI Document Translation is a cloud-based service that enables seamless and efficient language translation within documents. OCI Document Translation uses Oracle pre-trained Machine Translation models to perform language translation and other language-related operations.

Document Translation translates a variety of document types. Word, Excel and PowerPoint can be translated while keeping their original formatting. Plain text, HTML formats and JSON are supported, ideal for translating online content or integrating translation your global applications. Additionally, formats for closed captions and subtitling are supported, improving the accessibility of your video content.

Supported Document Types

Supported languages.

For list of supported languages, see Text Translation .

Translate user guides, blogs and knowledge base articles to reach a wider audience.
Improve internal communications and knowledge sharing across global teams.
Expand the reach of your sales and marketing campaigns by providing presentations and marketing assets in multiple languages.
Make your training content more inclusive to non-native speakers by adding subtitles to recorded video content.
Develop multi-lingual support for products and services, including expanding your machine learning models to be used with non-English input content.

Known Issues and Limitations

Oracle Translate provides good quality and reliable translation for a wide range of business enterprise and generic content. Translated documents can be utilized without further modification if some imperfections are tolerated. In cases where precision is essential, post-editing by native language speakers can be commissioned to rectify and enhance machine translation output.

To enhance the quality of your translations, consider these potential limitations and adopt the recommendations listed below:

Controlling Translation Features

Document Translation allows you to control and customize translation through Advanced Properties, either by using a glossary file or specific file properties.

A glossary is a list of user-supplied terms that can be used within the Document Translation service to control your translation. By using a glossary, you can specify how to translate or not translate certain terminology.

The main use cases for glossaries include:

Ensuring your context- and domain-specific terminology is translated consistently throughout your content.
Restrict certain terms or words from translation. For example, brand or product names that you don't want to translate.

File type specific properties, allow you to optionally control what elements of a file are translated. For example, columns to translate in a CSV file or elements to translate for a JSON file.

Open the navigation menu and click Analytics & AI . Under AI Services , click Language .
In the left-side navigation menu, click Jobs .
Click Create Job , and then enter a name and compartment.
Select the Pretrained language translation .
Select source language.
Select target languages.
Click Next .
Enter the Data type .
Enter the bucket where the document is located.
Enter the datafile name.
Enter the text column name of the column that has the text to be processed.
Enter the row ID column. This is the column that uniquely identifies the row.
(Optional) Enter the columns to be copied to output.
(Optional) Enter the Job output data.
To review details, click Next .
Click Create job .

Use the oci ai language batch-language-translation command and required parameters to translate one or more files:

For a complete list of flags and variable options for CLI commands, see the CLI Command Reference .

Run the BatchLanguageTranslation operation to translate one or more files.

Spotify adds new ‘AI Playlist’ feature that uses text prompts [Video]

Rolling out now in beta, Spotify is launching a new “AI Playlist” feature that uses text prompts to build a playlist based on a user’s description.

Joining in on the generative AI trend, Spotify’s new “AI Playlist” feature uses a user’s text prompt to create a playlist. Spotify offers a couple of examples including “an indie folk playlist to give my brain a big warm hug” and “relaxing music to tide me over during allergy season.”

Once the playlist is created, you can adjust what songs are in it, and even ask the AI to tweak the selection with requests such as “more pop” and “less upbeat.”

Spotify explains:

Starting with users on Android and iOS devices in the United Kingdom and Australia, creating a new playlist with AI Playlist is as simple as typing a unique prompt into the chat. Looking for “an indie folk playlist to give my brain a big warm hug,” “relaxing music to tide me over during allergy season,” or “a playlist that makes me feel like the main character”? AI Playlist has you covered.

For the time being, though, Spotify is releasing this feature in a region-limited beta. AI Playlist is, for now, only available in the UK and Australia, and only for Premium subscribers.

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An error occurred during translation: 500 Server Error: Internal Server Error

Hi, Long story short, using gpt-3.5-turbo for translating some text. I give json file to script which has bunch of objects, under key description theres text that needs to be translated. Worked fine, i did with couple of jsons, but then it started to not work. It gets the script running and like after 20 min it breaks. I get this error message:

"An error occurred during translation: 500 Server Error: Internal Server Error Response content: { “error”: { “message”: “Failed to create completion as the model generated invalid Unicode output. Unfortunately, this can happen in rare situations. Consider reviewing your prompt or reducing the temperature of your request. You can retry your request, or contact us through our help center at help.openai.com if the error persists. (Please include the request ID req_30208d9e72af21a2faa1cdf2394c4fd0 in your message.)”, “type”: “server_error”, “param”: null, “code”: “invalid_model_output” } }

Translation failed for the following description: bunch of text here from json which dont containt any strange char"

Sad thing is that ofcors it takes tokens from account, but it doesnt save the results up to that point where it breaks, so i need to just start all over from start… Also i tried setting temperature to 0.2 same result.

20 mins is a decently long time, esp for 3.5, for things to go wrong. Are you function chaining? If so, do you have any logs setup to know which functions complete successfully?

I guess its long, but some of json files that worked had like even more code and was working for 45-50 and finished the job. Not much of coder myself, know some basic stuff just to get job done…

import os import json import requests

openai_api_key = ‘key’

def translate_text(text): headers = { ‘Content-Type’: ‘application/json’, ‘Authorization’: f’Bearer {openai_api_key}’ } data = { “model”: “gpt-3.5-turbo”, “messages”: [ { “role”: “system”, “content”: “Please translate the following text into Serbian. All texts are about motorcycles. This words keep in english: cruiser, naked, swingarm, ride-by-wire. For this next words use this kind of translation: single seat = jedno sediste, floating = plutajuća, brake calipers = kočione čeljusti, six pistons = šest klipova, four pistons = cetiri klipova, radially mounted = montirane radijalno, dual seat = dvostruko sedište, a two-piece dual seat = dvostruko sedište, flagship = najprestižniji.” },

def translate_json_file(file_path): with open(file_path, ‘r’, encoding=‘utf-8’) as file: data = json.load(file)

folder_path = ‘C:\Users\Mile\Desktop\Arch’ json_file_name = ‘data.json’ json_file_path = os.path.join(folder_path, json_file_name)

translated_data = translate_json_file(json_file_path)

if translated_data: output_file_path = os.path.join(folder_path, ‘translated_’ + json_file_name) with open(output_file_path, ‘w’, encoding=‘utf-8’) as output_file: json.dump(translated_data, output_file, indent=4, ensure_ascii=False)

else: print(“Translation failed. No translated data saved.”)

Hmm this is a bit outside my area of expertise since I don’t know Serbian - perhaps there are characters in the text which 3.5 just can’t handle, or there is a bug in OpenAI’s side somewhere.

So regarding the actual issue, I don’t think I can help much to figure that out. Have you looked at the text in question? Have you ever seen the model successfully return a translation in Serbian for that text? I wonder if there is some issue with that particular text, some character or formatting that is particularly odd.

Anyway my best suggestion for now is to implement retries like this:

I wouldn’t normally suggest this, but if you are still getting issues, it may actually be worth reaching out to OpenAI to see if they can investigate.

Tnx for feedback.

Well as i said the strange thing is that it did the job before, then it started not to work anymore.

All json files before were even longer, and the prompt was the same, text in json is english, nothing new has been added/removed from equation.

So in error where it points to text in json where it stopped working, if i check it and even if i ask chatpt is something wrong here, everything is fine…

It would be a lot easier of didnt work at all, this way just dont know what to think…

One thing maybe is to try again json file that was successfuly translated before, but im pretty sure im gonna get a error again, like something has changed at their part.