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How to Use Google Translate for Text, Images, and Real-time Conversations

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• Wichita Technical Institute

In This Article

Jump to a Section

• Translate Text With Google Translate
• Translate Images
• Translate Words and Speech
• Translate Real-Time Conversations

How Many Languages Does Google Translate Support?

• Get Google Translate

What to Know

• For text: Select a language > Tap to enter text > begin typing > Enter .
• For spoken word: Select a language > tap the mic > begin speaking at the beep. Tap the Speaker icon to hear the translation.
• For conversations: Select a language > tap Conversation > begin speaking. Watch the screen for the translation.

This article explains how to use Google's Translate tool, which can handle text, images, speech, and even real-time conversations.

How to Translate Text With Google Translate

Translating text is the easiest and most well-supported function of Google Translate. Here's how to translate any text you come across.

Select the name of the source language you want to translate from in the top-left of the screen. In this example, we're using English .

Then select the name of the destination language you want to translate to in the screen's top-right. In this example, we're using Spanish .

Select the field that says Tap to enter text and either type or copy and paste (press and hold) the text you want to translate into this field.

You can also use the predictive text function to help write what you want to translate quicker.

The Google Translate app will continually translate what you're writing in the field underneath. At any time during this translation process, you can tap the Speaker icon to hear what it sounds like in your chosen translation language.

When you're finished typing you can use the right arrow or Enter key to return to the previous screen, then if you want to copy the translation, tap the three-dot menu icon and select Share .

How to Translate Images

Translating a foreign language from an image or picture using your camera or previous images is super handy when you're out and about. In our example, we'll use a food menu.

Select the source language and the translation language at the top of the screen. In this example, we are using Chinese to English .

Select the Camera icon.

Align what you want to translate in your camera window and select Instant .

If you want to translate an image you already have, select the Import button and then locate and select the image on your device. Then skip to Step 4 .

Google will translate the image on your device. It may take a moment for the translation to complete, but once it does, you'll be able to select individual words in the image to highlight their translation.

Some languages offer live translation, but others require a saved image. To scan and save a selection for translation, select the Scan button.

How to Translate Words and Speech

Translating what you say into a different language is one of the most useful features of Google Translate when traveling or just trying to learn a new language . Here's how to do it.

Select the source language and the translate to language at the top of the screen.

Tap the microphone icon and when prompted with a beep, begin speaking. Google will automatically translate your voice into text form.

Select the Speaker icon to hear the translation spoken back to you.

If you want to dictate what you say into a different language instead, select the Transcribe icon. Then begin speaking as before, and what you say will be translated into your destination language on screen.

Transcribing is different than dictating. When you're dictating, you're just using your voice instead of a keyboard or stylus to input data to be translated. When you're transcribing, you're creating a written output of your voice. Transcribing is especially useful if you need to send a message or write an email.

Tap the microphone and then begin speaking as before..

What you say will be translated into your destination language on screen. When you're finished speaking, tap the microphone again to end the transcription.

How to Translate Real-Time Conversations

You can also use Google Translate to facilitate a live conversation between you and someone who speaks a language you don't understand.

Select the source and destination languages at the top of the screen.

Select the Conversation icon. 

You can manually select the speaker's language at any one time to force the app to use that as the source or select the Auto button to allow the app to determine who is speaking at any one time.

Begin speaking. The translation of what you're saying will appear on screen, as will a translation for any replies from the person you are speaking to. This lets you both see what's being said in real-time.

Google Translate can translate about 103 different languages for text translation. Although not all of them are as natural as each other, and 59 are supported offline, it covers much of the world and its most populous languages.

New languages can often be added, so you can check out the complete list of languages supported on the Google site.

Real-time speech conversations support 43 distinct languages, while camera image translation is available in up to 88 languages. You might think handwriting is more challenging, but it supports 95 different languages.

How to Get Google Translate

To make the most of Google Translate, you'll need to download and install the app on your compatible Android or iOS device . Before beginning any of the instructions below, make sure the app is open and functioning.

Download for:

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Google Translate 4+

Text, photo & voice translator.

• #1 in Reference
• 4.3 • 75.7K Ratings

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Description.

Translate between up to 133 languages. Feature support varies by language: • Text: Translate between languages by typing • Offline: Translate with no internet connection • Instant camera translation: Translate text in images instantly by just pointing your camera • Photos: Translate text in taken or imported photos • Conversations: Translate bilingual conversations on the fly • Handwriting: Draw text characters instead of typing • Phrasebook: Star and save translated words and phrases for future reference Permissions notice: • Microphone for speech translation • Camera for translating text via the camera • Photos for importing photos from your library Translations between the following languages are supported: Afrikaans, Albanian, Amharic, Arabic, Armenian, Assamese, Aymara, Azerbaijani, Bambara, Basque, Belarusian, Bengali, Bhojpuri, Bosnian, Bulgarian, Catalan, Cebuano, Chichewa, Chinese (Simplified), Chinese (Traditional), Corsican, Croatian, Czech, Danish, Dhivehi, Dogri, Dutch, English, Esperanto, Estonian, Ewe, Filipino, Finnish, French, Frisian, Galician, Georgian, German, Greek, Guarani, Gujarati, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hmong, Hungarian, Icelandic, Igbo, Ilocano, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Kinyarwanda, Konkani, Korean, Krio, Kurdish (Kurmanji), Kurdish (Sorani), Kyrgyz, Lao, Latin, Latvian, Lingala, Lithuanian, Luganda, Luxembourgish, Macedonian, Maithili, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Meiteilon (Manipuri), Mizo, Mongolian, Myanmar (Burmese), Nepali, Norwegian, Odia (Oriya), Oromo, Pashto, Persian, Polish, Portuguese, Punjabi, Quechua, Romanian, Russian, Samoan, Sanskrit, Scots Gaelic, Sepedi, Serbian, Sesotho, Shona, Sindhi, Sinhala, Slovak, Slovenian, Somali, Spanish, Sundanese, Swahili, Swedish, Tajik, Tamil, Tatar, Telugu, Thai, Tigrinya, Tsonga, Turkish, Turkmen, Twi, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Welsh, Xhosa, Yiddish, Yoruba, Zulu

Version 8.5.0

• Several bug fixes and usability improvements

Ratings and Reviews

75.7K Ratings

AI makes it all up

I have used Google Translate for many years and some of the recent changes have frustrated me immensely. I use this primarily for Chinese language and often use the camera feature. Lately, it seems the app will not faithfully transcribe what is displayed, but will change the characters displayed. I can’t trust that the AI hasn’t decided to substitute what is displayed with something different and perhaps has changed the meaning, by even a slight, but significant amount. A faithful transcription will allow me to puzzle out what the meaning may by allowing me to review the characters displayed, not the characters that have been substituted. Also, with the same feature, I used to be able to view the characters in the photo and choose which characters to translate, but now, I can only choose the translated segments. If there is a way to view an untranslated version, other than sending it to the home page (with the already unreliable transcription of what is displayed), I haven’t figured it out.

Accessibility for Instructional Design

Google Translate is now a form of augmented reality and is adapted for educational purposes. This application provides users with tools to translate between languages and they now include an image option; users take a photograph of a sign, piece of paper, or other form of written text and receive a translation in the language of their choice. This augmented reality is ground breaking because this allows online learners to access content in other languages. The application also translates spoken word in real time, which allows all learners to access audio in written form, in their own language, online or in-person. This version of augmented reality that is adapted for education can be utilized in an online learning environment and can be utilized by instructional designers. One of the major challenges with instructional design is selecting the correct tools to build learning experiences. With this application, instructional designers are able to create a course in their own language and can make their lesson accessible to learners by recommending Google Translate for accessibility. I plan to utilize this in conjunction with my online lessons and videos in order to reach more students with diverse abilities and primary languages.

Horrible Application Given the Size of the Company

The Google translate app is a joke. There are very few apps that can lead someone to yell expletives while sitting in their kitchen trying to enjoy a cup of tea. Editing something you’ve written on the Google Translate App is a pitiful process filled with tapping the screen of your phone over and over attempting to unselect individual words or sentences. Sometimes it selects the entirety of what you’ve written and won’t allow you to unselect it without a fight. It’s unconscionable that the process for editing what you’ve written doesn’t follow every other smart phone format. Not only that, when you’ve finished writing of considerable length, in my case an email, and would like to highlight, copy and paste it, you will quickly realize you cannot highlight and scroll at the same time like you can on any other apple app that includes type. Instead, you’re forced to go through a ridiculous process of highlighting as much as you can see, pasting it, returning to the app, copying more and then pasting that. I repeated that process six time before I had copied my email over to gmail. If I had more time I would go into detail about the “define” tool that pops up unprovoked and further adds to the absolute farce that is the UX of this application. For a company like Google to have produced such a dysfunctional infuriating UI is truly shameful.

App Privacy

The developer, Google , indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .

Data Linked to You

The following data may be collected and linked to your identity:

• Contact Info
• User Content
• Search History
• Identifiers
• Diagnostics

Data Not Linked to You

The following data may be collected but it is not linked to your identity:

• Browsing History

Privacy practices may vary, for example, based on the features you use or your age. Learn More

Information

English, Afrikaans, Albanian, Arabic, Armenian, Azerbaijani, Basque, Belarusian, Bengali, Bosnian, Bulgarian, Cambodian, Catalan, Corsican, Croatian, Czech, Danish, Dutch, Estonian, Filipino, Finnish, French, Gaelic, Galician, Georgian, German, Greek, Gujarati, Haitian, Hebrew, Hindi, Hungarian, Icelandic, Igbo, Indonesian, Irish, Italian, Japanese, Kannada, Kazakh, Korean, Kyrgyz, Laotian, Latvian, Lithuanian, Macedonian, Malay, Malayalam, Maltese, Marathi, Mongolian, Nepali, Norwegian Bokmål, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Serbian, Shona, Simplified Chinese, Singhalese, Slovak, Slovenian, Spanish, Swahili, Swedish, Tajik, Tamil, Telugu, Thai, Traditional Chinese, Turkish, Ukrainian, Urdu, Uzbek, Vietnamese, Welsh, Yiddish, Yoruba, Zulu

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Highlight or right-click on a section of text and click on Translate icon next to it to translate it to your language. Or, to translate the entire page you're visiting, click the translate icon on the browser toolbar. Learn more about Google Translate at https://support.google.com/translate. By installing this extension, you agree to the Google Terms of Service and Privacy Policy at https://www.google.com/intl/en/policies. UPDATE (v.2.0): Now you can highlight or right-click a text and translate it vs. translate the entire page. You can also change extension options to automatically show translation every time you highlight text.

4.3 out of 5 42.9K ratings Google doesn't verify reviews. Learn more about results and reviews.

Jace Roesner Apr 10, 2024

Amazing If you need to translate a page this is the best one to get ( ͡° ͜ʖ ͡°)

Ira Evan Apr 9, 2024

Good. I've been using TinaMind GPT together for translation.

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Google Translate: Everything you need to know

W hen you think of Google’s core services, there are quite a few that come to mind. Many of you will think of Google Translate quite fast, though, that’s for sure. Google has plenty of software offerings that stand out, but Google Translate is easily one of the best-known ones. This translation service has been around since April 28, 2006. That makes it almost 18 years old at the time of writing this article. Back then it was categorized as a ‘statistical machine translation’ service, while it switched to a ‘neural machine translation’ service in 2016. In this article, we’ll talk more about Google Translate, to give you a better idea of what it is, and what it can do.

What is Google Translate?

Google Translate is basically a language translation service from Google. Or if you’d like a more scientific term, it’s a “ multilingual neural machine translation service ”, as indicated on Wikipedia. It’s actually one of the best-known language translation tools out there, if not the best-known one. Basically everyone I personally know uses Google Translate for translation needs, I don’t think I’ve ever heard anyone mention anything else in day-to-day life. There are other offerings out there, which we’ll talk about later on, but Google Translate is very popular.

What platforms is Google Translate available on?

You can access Google Translate in an app form, and also via your web browser . When it comes to apps, Google Translate is available on both Android and iOS, to of the largest mobile operating systems out there. You can also access it via basically any desktop operating system, simply navigate to https://translate.google.com/ , and you’ll have access to its services. Using it is also very simple.

Do note that you may not be able to use the Google Translate app on just any Android smartphone. The device needs to have Google services. So it either needs to come with Google Play Store pre-installed, or in case if you’re importing a device from China, it needs to have support for Google services. The app likely won’t work on devices from Huawei, unless you’re using an emulator like GSpace. Why? Well, due to the US ban. Huawei is blocked from using Google services on its devices.

What are Google Translate’s competitors/alternatives?

Are there any competitors to Google Translate out there? Well, yes, and you may have even heard of some of them. The Microsoft Translator is a good example of competition for Google Translate. It can translate well over 100 languages, and it has a nice app you can use. It also has some benefits if you plan on using it on your website, over Google Translate. Its API lets you translate more characters than Google Translate (for free), for example.

Another good example of a competitor is Amazon Translate . It’s a part of Amazon Web Services, though it’s mostly focused on API usage, so it’s not exactly the same. Amazon Translate also has a higher monthly limit than Google Translate when it comes to API usage, the same as the Microsoft Translator. Looking at it as a personal translation tool, however, it’s not exactly a competitor to Google Translate or Microsoft Translate.

Yandex Translate is another great choice. It doesn’t translate nearly as many languages as Google Translate or Microsoft Translator, but its pricing is the advantage here if you plan on using it on your website or something like that. API usage is paid only, though, it’s no longer free, as is for Google Translate and Microsoft Translator (with limits).

Can I use Google Translate if I’m not connected to the Internet?

Is it possible to use the tool without an Internet connection? Well, yes, but only if you use an app, it’s not possible on the web. Why? Well, because you need to download the languages you’re interested in first. If you want to translate a language you didn’t download for offline use, you’ll need an Internet connection. You can easily download them via the Google Translate app, though. Simply open the app, and tap the section with languages at the bottom (either left or right). Once you do that, you’ll see a drop-down menu and a download icon next to various languages. Tap that icon and download the language you need. That way you’ll be ready to go if you’re traveling abroad or something like that.

What is the first thing you should do in Google Translate before you start using it?

This actually ties into the previous section, downloading languages. There’s really only one thing you should do before you start using the app, download the languages you need. This only applies if you expect to be out of the Internet connection at some point while needing the Google Translate app. Many people only download Google Translate when they’re traveling somewhere, so its usage in offline mode is presumably quite high. If that’s the case for you, make sure you download the languages you’ll need. That’s basically the only thing you should do in order to prepare the app for usage.

Is the Google Translate app free to use?

The answer to this is both yes and no. How come? Well, the app is completely free to use for personal use. If that’s what you’re looking for, you’re good. If you plan on using it on your website and need API usage, then it’s free to use up to a certain degree. Google Translate API free tier lets you translate up to 500,000 characters per month. If you expect that the limit will go over that, you’ll need to pay up for Google Translate API usage. The vast majority of you reading this will probably use it as a personal translation tool. If that’s the case, you have nothing to worry about.

What are the best features of Google Translate?

Needless to say, Google Translate is all about translation. All of its features are related to various translations, so that’s what we’ll talk about here. Google Translate does offer plenty of choices in that regard, text is only one of them. So, let’s see what’s on offer.

Offline access

The first feature worth noting is the offline access for your translating needs. As mentioned in an earlier chapter, you can download specific languages offline, so that you always have access to them. Many times when you travel you don’t have access to the Internet at all times, which is where such an option is welcomed. This is basically a must-have feature for an application that handles language translations.

Basic text translation

Google Translate does support basic text translations . That’s the basic feature of this app and the first one that was made available. You can simply type in what you need translate, or paste text from a different app, website, or wherever you want. Make sure to select the language that the text comes from and the language you want the app to translate it to. You can also let the app figure out what language it is, in case you don’t know.

Voice translation / conversation

Voice translation allows you to speak to someone who speaks a different language. All you need to do is fire up an app and tap the ‘Conversation’ option in the bottom-left corner. That will enter the conversation mode where you’ll be able to set the parameters and start talking to a person who speaks a different language. Do note that there’s also an option for you to speak into the microphone, and for the app to translate what you said (or someone else). That option is highlighted with a large microphone icon, it’s located next to the ‘Conversation’ option.

Camera translation

The third option at the bottom of the screen within Google’ translation app is ‘Camera’. It’s located in the bottom-right corner, and it’s the last one of the magic trio down there. If you tap this option, a camera UI will appear, and you’ll be able to point it to the text you need to translate. Google Translate will do the heavy lifting for you even without you snapping a photo, it’ll translate text in real-time.

Handwriting translation

Google Translate also supports handwriting translation. You can simply use your handwriting in order to write something that needs translating, and that’s it. This is also very convenient if you need something to be translated and there’s no letter on your keyboard. If we’re talking about a different alphabet or something like that.

Website translation

What if you need Google Translate to translate an entire website for you? Well, that’s not a problem either. It’s very simple, copy and paste the URL of a website you need translated into Google Translate, and the app will handle things for you. This is also a rather common use case for this tool, and it improved a lot over time.

Translations of text inside files

Google’s translation service also allows you to translate files. For example, if you have a PDF document that you don’t really understand, and need to read it in a different language, that’s not a problem. You can simply upload that document to Google Translate, after which the tool will analyze it, and offer you the translated version.

The post Google Translate: Everything you need to know appeared first on Android Headlines .

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Exploring Google Translate-friendly strategies for optimizing the quality of Google Translate in academic writing contexts

Yu-chih sun.

Institute of Teaching English to Speakers of Other Languages, National Yang Ming Chiao Tung University, 1001 University Rd., Hsin-chu, 300 Taiwan

Fang-Ying Yang

Hsin-ju liu, associated data.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

The present study explored the types of errors found in Google Translate (GT) Chinese-to-English translations and, based on those error types, proposes strategies for optimizing the performance of GT. Seven abstracts written in both Chinese and English from seven articles published in English Teaching and Learning in 2017 were selected as the materials. The researchers compared the GT translations to the English abstracts written by the original author(s) and analyzed the problems in the translations. The problematic translations consisted of grammatical errors (35%) and lexical errors (65%). Relatedly, we propose nine specific strategies to employ when writing Chinese abstracts to be translated into English using GT. According to the strategies, we suggest that users (1) avoid native language-specific expressions, (2) maintain the use of original English terminologies in composing Chinese abstracts, and (3) enhance logical relations and expressions for the discipline-specific discourse community. Further analyses revealed that 99% of the 69 identified problems in the GT translations of the seven abstracts could be avoided by using the proposed strategies. A conceptual framework for the collaboration between GT and GT users is proposed and pedagogical implications are discussed.

Introduction

The United Nations’ (UN) 2030 Agenda for Sustainable Development serves as a guideline “for peace and prosperity for people and the planet” (Department Economic and Social Affairs of the United Nations, History section 2022 ). The current 17 Sustainable Development Goals (SDGs) outlined in the agenda stressed the importance of global partnerships, which require all countries to work together to recover from the negative impact of the COVID-19 pandemic (Department Economic and Social Affairs of the United Nations 2022 ). At the heart of the global partnerships lies effective intercultural communication in which language is one of the major means. Learning a new language, however, is a time-consuming process and is often constrained by a number of factors (van Lieshout and Cardoso 2022 ). With the rapid development of technology, a variety of tools have been adopted by learners to facilitate the process of language learning. An understanding of the affordances of these tools can guide the language learners to make evidence-based decisions in selecting and using the tools. The present study focuses on one of the commonly used technological tools by language learners and users, Google Translate (GT). The purpose of the study is to explore GT’s affordances in English academic abstract writing by first analyzing the translation problems by GT, and based on which, proposing nine GT-friendly writing strategies for language learners to employ when they use GT to support their English abstract writing.

Advantages of machine translation technologies

With recent development of artificial intelligence (AI), the neural machine translation system utilized by machine translation (MT) tools such as Google Translate (GT) has greatly improved the translation accuracy and quality. This improvement has led to better translations of longer texts (Ducar and Schocket 2018 ). Studies have indicated that GT can be a useful learning aid for college students in English-as-a-Foreign-Language (EFL)/English-as-a-Second-Language (ESL) contexts (Nila and Susanto 2017 ; Tsai 2019 ). Recent research shows that GT is a promising tool for learning second language (L2) vocabulary and pronunciation in self-directed settings (van Lieshout and Cardoso 2022 ). MT has recently taken on increasing importance in scholarly fields such as L2 academic writing and publishing. Previous research shows that MT helped L2 writers improved the quality (Stapleton and Kin 2019 ) and quantity of their L2 writing (Chon and Shin 2020 ). Groves and Mundt ( 2015 ) explored GT’s effectiveness in providing writing instruction in an English for academic purposes (EAP) context. They asked students to write short essays in their first language, and then they translated the essays to English with GT. The results showed that despite the fact that they still contained ungrammatical words and sentences, GT’s translations were considered comprehensible; the results even met the minimum admission standards for most academic institutions in Malaysia. In addition to improving L2 learners’ writing outcomes, MT also offers affective supports to L2 learners in the process of L2 writing by lowering their anxiety levels and enhances motivation and confidence (Lee 2020 ).

Challenges of machine translation technologies

Despite MT’s positive effects, studies (e.g., Alhaisoni and Alhaysony’s 2017 ) found that students expressed a paradoxical view toward its use in class. Teachers often have divided opinions regarding MT’s role in language learning. Jolley and Maimone ( 2015 ) reported that both students and their teachers have positive outlooks with regard to the in-class integration of MT; they also suggested that, in the future, teachers should provide guidance during the learning process in order to facilitate more appropriate use of the tool. On the other hand, some instructors still hold conservative, even antagonistic, views regarding the use of MT in class (Stapleton and Kin 2019 ). Chandra and Yuyun ( 2018 ) suggested that it is important for instructors to cover both the benefits and the limitations of using MT in class so that students can engage in productive and meaningful translation activity and language practice. In summary, specific guidelines of effective and appropriate MT use are called for. The present study responds to the call by offering MT-friendly writing strategies based on empirical evidence.

Evaluation and measurement of machine translation quality

Lee ( 2021 ) systematically reviewed and conducted meta-analysis on MT studies related to foreign language education published between 2000 and 2019. Based on the review of the studies that examined MT translation quality, Lee ( 2021 ) found that overall the most common error types produced by MT were syntactic and grammatical errors, and the translation quality was particularly poor with translation of longer texts. However, closer examinations of more recent studies reveal that the application of the neural machine translation system in MT has greatly improved the translation quality of longer texts.

Lee ( 2021 ) also indicates that, unlike the evaluation of MT outcomes in translation-related studies, the purpose of evaluating the MT translation quality in L2 learning and teaching mainly focuses on examining MT’s technological affordances for L2 learning and teaching rather than evaluating the translation quality per se. As a result, most studies evaluate students’ writing after students used MT as a supporting tool rather than directly evaluating the quality of machine translation output. For example, Tsai ( 2019 ) used two online computational writing assessment tools to assess L2 students’ MT-supported English writing. In this study, writing quality was evaluated in terms of the number of spelling and grammatical errors, the probability of errors, and lexical features (i.e., the number of words at different frequency bands and lexical density). In another study, Stapleton and Kin ( 2019 ) recruited English teachers to evaluate the quality of English essays, which were originally composed by students in their L1 (Chinese) and later translated by GT into English. A rubric on a four-point scale covering three dimensions (i.e., grammar, vocabulary, and comprehensibility) was developed to guide the teachers to evaluate the translated English text.

Previous studies show that GT has frequently been integrated into English writing classes and used as a support tool by language learners. Given the fact that GT has advanced to become a more reliable tool, and will continue to advance further, its application in the field of language learning and teaching deserves our attention. The present study, therefore, sought to explore the affordances of GT in language learning and teaching and based on which to propose strategies for enhancing its affordances by addressing the following three research questions:

• What types of errors in English translation can be identified when GT is used to translate Chinese academic abstracts?
• What Chinese abstract writing strategies can be used to optimize the quality of GT English translations?
• To what extent can the proposed Chinese abstract writing strategies enhance the quality of GT English translations?

Seven abstracts (containing a total of 51 Chinese sentences and 2129 Chinese characters) written in both Chinese and English from seven articles published in English Teaching and Learning ( ETL ) in 2017 were selected as the materials for data analysis. ETL was chosen because the journal’s corresponding English abstracts allowed the researchers to check the accuracy of terminologies translated by GT. Also, the topics of studies published in ETL match the researchers’ field of expertise. The researchers’ familiarity with the content knowledge of the abstracts, thus, allowed for the accurate and reliable justification of the GT translations.

Data analysis

To answer Research Question 1, the researchers first used GT to translate the seven Chinese abstracts into English. The English translations generated by GT were then compared to the English abstracts written by the studies’ author(s). Differences between each Google translated English abstract and the corresponding original English abstract were identified, with those differences used to identify and code errors in the translation. Grounded theory (Glaser and Strauss   1999 ) was employed as an analytical approach. The process of data analysis was inductive, iterative, and data driven. A research assistant, who had a master’s degree in the Teaching English as a Second Language (TESOL), coded the errors and developed an initial coding system. The final coding system was developed through several rounds of data examination and discussion with the first author, who had a Ph.D. degree in TESOL.

To answer Research Question 2, the researchers examined each error in the English translations and identified the source(s) of the errors, before then using that information to modify the corresponding portion of the Chinese abstract written by the author(s). The modification strategies were coded and analyzed inductively following the same approach described in the previous paragraph.

To answer Research Question 3, the researchers used GT to translate the modified Chinese abstracts into English. Each entry of the English output was rated by the researchers to evaluate the translation outcome. More specifically, the evaluation focused on whether the use of a given modification strategy successfully resolved the errors in the English translations. A total of 69 problems in the GT translations were evaluated. A check of interrater reliability regarding all 69 entries was conducted, and it was found that the interrater reliability was 100%.

Types of errors in the GT English translations

Sixty-nine problems in the GT translations were identified (Table ​ (Table1). 1 ). Approximately 34.8% of those errors were categorized as grammatical errors, while 65.22% were categorized as lexical errors. The most common grammatical errors were instances of mispunctuation, null-subject sentences, and the misuse of conjunctions. The most common lexical errors were instances of academically inappropriate word choices; non-contextual, literal translations of Chinese texts; and untranslated or redundant/unnecessary words.

Types of errors in the GT translations

N  = 69

Optimization strategies for Chinese abstract writing

Nine optimization strategies for Chinese abstract writing were identified based on inductive analyses of the GT translation errors. The nine strategies (Table ​ (Table2) 2 ) can be divided into three types of actions: (1) avoidance actions: Strategies 1–3 (2) maintenance actions: Strategy 4, and (3) enhancement actions: Strategies 5–9. Each strategy is illustrated as follows:

Optimization strategies

Strategy 1: avoid using Chinese big words or set phrases, use modern Chinese

Our analyses showed that GT currently cannot appropriately process Chinese big words and ancient literary Chinese. As shown in Table ​ Table3, 3 , one author used the Chinese word 服膺 (fú yīng; obey ) to indicate that the students in the study identified with the core value of their textbooks. Nevertheless, Google translated the Chinese word 服膺 to clothing , an uncontextual translation which totally deviated from the Chinese word’s actual meaning. The researchers then replaced 服膺 with a more modern word, 認同 (rèn tóng ; identify ). The modified Chinese text, thus, generated a contextually appropriate GT English translation—“… most children agree with the value and content of textbooks.” Of the 69 translation errors, three (4.3%) could be resolved using this strategy.

Strategy 2: avoid writing null-subject sentences

Writing a sentence without a subject is common in Chinese. The data analyses of the present study showed that GT assigned contextually inappropriate subject(s) to null-subject sentences. The associated proposed strategy recommends that the writing of null-subject sentences in Chinese, especially long, complex sentences, be avoided. As shown in Table ​ Table4, 4 , the original Chinese text consisted of a null-subject sentence. GT assigned a contextually inappropriate subject, you , to the sentence. To avoid this problem, we added a contextually appropriate subject 研究者 (yán jiùzhě; the researchers ) to the sentence. The resulting GT output was, thus, acceptable. Of the 69 translation errors, seven (9.4%) could be resolved using this strategy.

Strategy 3: avoid using Chinese-specific punctuations

The analyses showed that GT followed the original Chinese punctuations, which generated incorrect uses of punctuation in the English translations, especially in cases of listing. As can be seen in Table ​ Table5, 5 , we used a conjunctive coordinator, 及 (jí; and ), and a Chinese-specific punctuation mark that indicates a short pause (、) to separate three nouns in the original Chinese sentence. GT then simply used a comma to replace the Chinese-specific punctuation (、) without placing a conjunctive coordinator, and , before the last listed item. The researcher modified the Chinese text by following the English punctuation rule for listing and using commas instead of the Chinese-specific one. The modified GT English translation outcome was, thus, correctly punctuated. Four of the 69 (4.3%) translation problems were resolved using this strategy.

Strategy 4: use English terminologies directly

Strategy 4 suggests the use of English terminologies instead of Chinese terminologies when writing Chinese that is to be translated into English using GT. As shown in Table ​ Table6, 6 , Google translated 修辭言步 (xiū cíyánbù) as rhetoric step and translated 介紹本研究 (jiè shàoběnyán jiù) as introducing this study. Although the translation output was still comprehensible, it deviated from the standard usage of the terms in this field of study. In this case, the English terms rhetorical move and occupying the niche can be used directly in Chinese abstract writing to avoid nonstandard GT translations of the terminologies. Approximately 30% of the English translation errors could be addressed using this skillful bilingual writing strategy.

Strategy 5: add the structural particle “的” ( de ) after compound-complex adjectives/adjectival phrases to distinguish the modifier from the modified noun

In Chinese, it is common to attach the attributes of a noun by directly adding complex adjectives or complex adjectival nouns before it. The analyses showed that GT was not able to distinguish the complex adjectival nouns from the nouns that they were intended to modify. Table ​ Table7 7 illustrates the use of Strategy 5, inserting the structural particle 的 ( de ) between the modifier from the modified noun, to overcome this problem. As shown in Table ​ Table7, 7 , 學習成效 (xué xíchéng xiào; learning effectiveness ) was modified by adjectival nouns, 跨文化溝通能力 (kuàwén huàgōu tōngnéng lì; cross-cultural communication skills ). GT translated the entire phrase into cross-cultural communication skills learning effectiveness without identifying that 學習成效 (xué xíchéng xiào; learning effectiveness ) was the noun to be modified. We inserted the structural particle 的 ( de ) between the complex adjectival nouns and the modified noun. GT, thus, successfully identified that 學習成效 (xué xíchéng xiào; learning effectiveness ) was the modified noun and generated an appropriate translation for the phrase— learning effectiveness of cross-cultural communication skills. The analyses showed that Strategy 5 could be applied to four of the 69 (5.8%) translation errors.

Strategy 6: use circumposition such as “在…中” (zài…zhōng) to mark the abstract context where an event takes place

Circumposition combines the usage of a preposition (e.g., on the floor) and a postposition (e.g., 4 hours ago ) to create a phrase specifying the place where an action takes place. In other words, circumposition refers to the use of two prepositions in a prepositional phrase: one at the beginning of the phrase, and one at the end. In Chinese, it is common to use circumposition to surround a complement to indicate that an event takes place in abstract locations or contexts. Our data analyses showed that using Chinese circumposition to specify abstract contexts can enhance the clarity of GT English translations. As shown in Table ​ Table8, 8 , the context identified in the sentence was an abstract context, 學術寫作 (xué shùxiě zuò; academic writing ). In the original Chinese text, the author only used a preposition, 在 (zài; in ), to indicate the context. The GT placed the resulting prepositional phrase, 在學術寫作 in academic writing , at the end of the sentence, which resulted in an ambiguous sentence; the elements which form the object of the sentence were separated into two: the relationship between the presentation and coherence and in academic writing. The structure of circumposition, 在學術寫作中 in academic writing , was added to the modified Chinese text. Although the English translations of 在學術寫作 ( in academic writing ) and 在學術寫作中 ( in academic writing ) were the same, the use of circumposition in the Chinese text generated a much clearer English sentence in which the elements which formed the object of the sentence were more consolidated.

Strategy 7: use a coordinating conjunction such as “並(且)/而(且)” (bìngqiě/érqiě) to introduce additional ideas

Explicitly marking relations between phrases or clauses can enhance the clarity of GT output. As shown in Table ​ Table9, 9 , the original Chinese text included three verb phrases without linking them with any coordinating conjunctions. The logical relations of the three verb phrases were not explicitly specified. GT, thus, translated the second verb phrase into two separate verb phrases, which deviated from the meaning of the original text. In the modified Chinese text, a coordinating conjunction, 並 ( and ), was added to introduce the third verb phrase. The addition of the coordinating conjunction resulted in an accurate translation of the three verb phrases.

s subject, vp verb phrase, c conjunction

Strategy 8: use an infinitive phrase such as “以/來”(yi/lai; in order to) to suggest that the latter clause marks the purpose of the former clause

Like Strategy 7, Strategy 8 can also be used to explicitly mark the logical relations between clauses. Table ​ Table10 10 illustrates an example of using an infinitive phrase, 以 or 來 ( in order to ), to introduce a purpose clause. In the original Chinese text, the author used a coordinating conjunction, 並 ( and ), to introduce a clause that was supposed to indicate a purpose. GT was unable to precisely translate this rhetorical move. An infinitive phrase, 以 ( in order to ) was used to replace 並 ( and ) in the modified Chinese text. The modified GT English translation, thus, produced a to-infinitive clause that properly introduced a purpose.

Strategy 9: use academically appropriate vocabulary and phrases instead of colloquial expressions

As shown in Table ​ Table11, 11 , in the original Chinese text, the author chose the Chinese word 訪問 (fǎng wèn) to indicate interview ; however, the word 訪問 carries other general, colloquial meanings such as visit . Such a word choice resulted in an unprofessional GT translation in this context— visit . According to the proposed strategy, the word 訪問 was replaced by 訪談 (fǎng tán), a more specific one meaning interview in Chinese academic writing. The modified Chinese text, thus, generated an accurate GT English translation. The inductive analysis showed that a total of 11 (15.9%) of the GT translation errors could be avoided by using this strategy.

Evaluation of the Chinese optimization strategies

Each portion of the modified English output was evaluated. The evaluation focused on whether the use of the given modification strategy successfully avoided the problematic English translation output. Among the 69 identified problems in the GT translations, 68 were avoided using the proposed strategies. This finding indicates that the proposed optimization strategies can be used to resolve approximately 99% of the problems in GT English translations.

Discussion and conclusion

The present study explored the types of errors found in English translations produced by GT and proposes the use of various strategies to enhance the quality of GT translations. The results showed that using the nine GT strategies introduced in the study to modify the Chinese input into GT can correct approximately 99% of the errors in the original English translations. In other words, the findings of the study revealed that by understanding the capabilities and limitations of GT and understanding their own capabilities and limitations, GT users can utilize strategies that effectively compensate for both types of limitations and optimize the performance of GT.

In Fig.  1 , Zone 1 is the area in which both the user and GT can perform well. Zone 1 can be enlarged either through the user’s development of proficiency in the target language or through the advancement of the technology employed by GT. Zone 2 is the area in which GT still does not perform well but the user’s capability in the language can compensate for the limitations of GT. Zone 3 is the area in which the user can employ various strategies to enhance the quality of GT’s performance and therefore exceed his or her own limitations. This zone has been identified in previous studies; for example, GT was shown to outperform EFL users in terms of the use of precise vocabulary (Stapleton and Kin  2019 ; Chandra and Yuyun 2018 ). By using the nine strategies developed in this study, users can maximize the capability of Zone 3 and generate satisfactory translations. Finally, Zone 4 is an area that shows the limitations of GT. This zone can be reduced by growing Zones 1, 2, and 3. That is, the development of language proficiency, the skillful use of strategies to enhance the performance of GT, and the advancement of GT itself can lessen the size of Zone 4.

Conceptual framework of cooperation between users and Google Translate

Function-oriented language learning and teaching

As presented in Zone 3 in Fig.  1 , from a function-oriented perspective, the proposed strategies do not require fully proficient language skills. With partial, general knowledge of the target language, users can better utilize GT to reach the goal of effective communication, unlike traditional language teaching pedagogy where teachers take time to guide students in a step-by-step manner to develop academic writing skills. This requires a long developmental process for a learner to reach the proper level of communicative competence in order to participate in the discourse community of academic writing. With the help of GT, it is possible for learners who have only limited language proficiency in the target language but strong research ability, profound discipline-specific knowledge, and knowledge of the relevant terminologies in the target language to be empowered and given the access necessary to contribute their research findings to the field, thereby speeding up the creation and dissemination of knowledge.

New lingua franca

This vision of skillful user collaboration with GT to achieve effective communication may redefine the concept of a lingua franca in the future. With the swift development of GT, the term lingua franca might no longer refer to any particular language; instead, lingua franca could actually refer to the use of one’s first language along with appropriate GT strategies. That is, the new definition of lingua franca should be applicable to any language as long as it is written in a form that can effectively be translated into any other language through machine translation. In other words, the new lingua franca could be any language as long as it is written in a form with high machine readability.

Pedagogical implications

The concept of collaborating with GT using appropriate strategies may further transform the role of language learners into that of functional language users who could carry out real-life communication by skillfully drawing from their knowledge of their first language and the target language. This advancement may fundamentally change our beliefs about language teaching and learning. The collaboration between GT and language users is not meant to override the need for L2 learning or eradicate current practices of English academic writing. Instead, a shift of instructional focuses would become the priority. For example, English academic writing classes could potentially reduce the levels of laborious skill practice and training currently employed to teach some linguistic functions which GT can handle better, such as the use of tenses and definite/indefinite articles. More training could focus instead on aspects of language that GT currently cannot handle well, such as logical connections between ideas. Also, as the present GT technology is still far from being able to generate error-free translations (Ducar and Schocket 2018 ), L2 learners who use GT to support their writing still need to be competent in identifying and correcting problematic translations. In other words, users still need to learn the target language to be able to effectively evaluate the GT output. However, learners may no longer need to master a language before they can produce academic text with high readability if they assume an active, not a passive, role as a GT user through the use of the nine strategies proposed in the study.

Limitations and future research

The present study has several limitations which could be used to inform the objectives of future research. First, the GT strategies proposed by the study were proposed based on the analyses of problematic GT translations. Further empirical data are needed to examine the effectiveness of the proposed strategies. Second, it is still unclear how the strategies will be used by language learners. Future studies could employ qualitative research methods such as using think-aloud protocols to gain insights into learners’ use of the strategies and to examine the effectiveness of the strategies. The findings of such research could shed new light on the integration of these strategies into future curriculum and lesson designs of EAP courses. Also, as previous studies have shown that learners with different levels of language proficiency can take advantage of GT to various extents, it is important to explore how individual differences in factors such as language proficiency and attitudes toward GT-assisted writing influence the effective use of the proposed GT strategies. Moreover, the translation data used in the present study and the proposed strategies were limited to English academic writing. Future studies could explore specific GT strategies for different writing genres. Finally, to realize the vision of using one’s own language as a lingua franca, the collaboration between GT and users will have to be explored in more language pairs in the future, as the present study was limited to English-Chinese translation alone.

This work was supported by Ministry of Science and Technology, Taiwan [Grant No. 108-2410-H-009-018].

Data availability

Declarations.

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Contributor Information

Yu-Chih Sun, Email: wt.ude.ucyn@cynus .

Fang-Ying Yang, Email: wt.ude.ucyn@gnayf .

Hsin-Ju Liu, Email: moc.liamg@5274480v .

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Google Discontinues Translate Community Contribution Feature

• Google has discontinued the Translate Community Contribution feature.
• The decision comes as Google Translate has seen improvements due to advanced machine learning techniques.
• Users can still provide feedback directly through the Google Translate apps and desktop version to help improve translations.

Google announced that it’s shutting down the Contribute feature for Google Translate, which allowed users to suggest translations to improve the tool’s quality.

The decision comes as Google Translate has seen significant advancements in recent years, mainly due to the evolution and learning of its underlying systems.

The Launch Of The Contribute Feature

Launched in 2014, the Contribute feature was designed to leverage the knowledge of language enthusiasts and native speakers to enhance translations for the 80 languages supported by Google Translate.

Users could participate in the Translate Community by generating new translations, rating existing ones, and providing feedback on improving the service.

In a statement , Google acknowledged the value of user contributions, saying, “When Contribute first launched, real speakers often provided helpful translation suggestions when Translate missed the mark.”

However, Google believes that the improvements made to the service have removed the need for this feature.

Now. when navigating to translate.google.com and clicking on Contribute, you’ll see a message about its discontinuation:

New System For User Feedback

Moving forward, Google Translate users can provide feedback directly through the Android and iOS apps and on the desktop version when they feel a translation could be improved.

Google believes this new system will maintain the quality of the service while reducing the reliance on the Contribute feature.

When the feature was first introduced, it was seen as an innovative way to engage users and tap into the collective knowledge of language communities worldwide.

As Google Translate matured, the company developed machine learning techniques, such as neural machine translation, which greatly enhanced the accuracy and fluency of translations.

These technological advancements allow Google to provide higher-quality translations without relying as much on user contributions.

Looking Ahead

While the Contribute feature may be gone, Google remains committed to delivering accurate and reliable translations.

Google’s innovation in language technology means Translate will continue to be a valuable tool for breaking down language barriers and facilitating global communication.

How does Google plan to maintain the quality of its translations after discontinuing the Contribute feature?

Google intends to sustain the quality of its translation services through the following means:

• Continued advancement in machine learning, including neural machine translation technology, enables higher-quality translations.
• Implement a new feedback system where users can report translation issues directly via Google Translate’s Android and iOS apps and the desktop version.

What was the original purpose of Google Translate’s Contribute feature, and how has it evolved?

The Contribute feature was established with these objectives and has evolved as follows:

• Launched in 2014 to engage language enthusiasts and native speakers in enhancing translation quality for 80 languages.
• Provided a platform for users to suggest new translations, rate existing ones, and offer optimization feedback.
• It evolved with Google’s language technology to the point where user-generated contributions became less critical due to improved machine learning techniques.

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Matt G. Southern, Senior News Writer, has been with Search Engine Journal since 2013. With a bachelor’s degree in communications, ...

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