Tag Archives: Google Translate

Speak easy while traveling with Google Maps

Google Maps has made travel easier than ever before. You can scout out a neighborhood before booking a hotel, get directions on the go and even see what nearby restaurants the locals recommend thanks to auto-translated reviews.

But when you're in a foreign country where you don't speak or read the language, getting around can still be difficult -- especially when you need to speak with someone. Think about that anxiety-inducing time you tried to talk to a taxi driver, or that moment you tried to casually ask a passerby for directions.

To help, we're bringing Google Maps and Google Translate closer together. This month, we’re adding a new translator feature that enables your phone to speak out a place's name and address in the local lingo. Simply tap the new speaker button next to the place name or address, and Google Maps will say it out loud, making your next trip that much simpler. And when you want to have a deeper conversation, Google Maps will quickly link you to the Google Translate app.

Google_SpeakEasy_GIF_191018.gif

This text-to-speech technology automatically detects what language your phone is using to determine which places you might need help translating. For instance, if your phone is set to English and you’re looking at a place of interest in Tokyo, you’ll see the new speaker icon next to the place’s name and address so you can get a real-time translation. 

The new feature will be rolling out this month on Android and iOS with support for 50 languages and more on the way. 

Source: Translate


Google Translate’s instant camera translation gets an upgrade

Google Translate allows you to explore unfamiliar lands, communicate in different languages, and make connections that would be otherwise impossible. One of my favorite features on the Google Translate mobile app is instant camera translation, which allows you to see the world in your language by just pointing your camera lens at the foreign text. Similar to the real-time translation feature we recently launched in Google Lens, this is an intuitive way to understand your surroundings, and it’s especially helpful when you’re traveling abroad as it works even when you’re not connected to Wi-Fi or using cellular data. Today, we’re launching new upgrades to this feature, so that it’s even more useful.

Instant camera translation.gif

Translate from 88 languages into 100+ languages


The instant camera translation adds support for 60 more languages, such as Arabic, Hindi, Malay, Thai and Vietnamese. Here’s a full list of all 88 supported languages.

What’s more exciting is that, previously you could only translate between English and other languages, but now you can translate into any of the 100+ languages supported on Google Translate. This means you can now translate from Arabic to French, or from Japanese to Chinese, etc. 

Automatically detect the language

When traveling abroad, especially in a region with multiple languages, it can be challenging for people to determine the language of the text that they need to translate. We took care of that—in the new version of the app, you can just select “Detect language” as the source language, and the Translate app will automatically detect the language and translate. Say you’re traveling through South America, where both Portuguese and Spanish are spoken, and you encounter a sign. Translate app can now determine what language the sign is in, and then translate it for you into your language of choice.

Better translations powered by Neural Machine Translation

For the first time, Neural Machine Translation (NMT) technology is built into instant camera translations. This produces more accurate and natural translations, reducing errors by 55-85 percent in certain language pairs. And most of the languages can be downloaded onto your device, so that you can use the feature without an internet connection. However, when your device is connected to the internet, the feature uses that connection to produce higher quality translations.

A new look

Last but not least, the feature has a new look and is more intuitive to use. In the past, you might have noticed the translated text would flicker when viewed on your phone, making it difficult to read. We’ve reduced that flickering, making the text more stable and easier to understand. The new look has all three camera translation features conveniently located on the bottom of the app: “Instant” translates foreign text when you point your camera at it. "Scan" lets you take a photo and use your finger to highlight text you want translated. And “Import” lets you translate text from photos on your camera roll. 


To try out the the instant camera translation feature, download the Google Translate app.

Source: Translate


Providing Gender-Specific Translations in Google Translate



Over the past few years, Google Translate has made significant improvements to translation quality by switching to an end-to-end neural network-based system. At the same time, we realized that translations from our models can reflect societal biases, such as gender bias. Specifically, languages differ a lot in how they represent gender, and when there are ambiguities during translation, the systems tend to pick gender choices that reflect societal asymmetries, resulting in biased translations. For instance, Google Translate historically translated the Turkish equivalent of “He/she is a doctor” into the masculine form, and the Turkish equivalent of “He/she is a nurse” into the feminine form.

Recently, we announced that we’re taking the first step at reducing gender bias in our translations. We now provide both feminine and masculine translations when translating single-word queries from English to four different languages (French, Italian, Portuguese, and Spanish), and when translating phrases and sentences from Turkish to English.
Gender-specific translations on the Google Translate website.
Supporting gender-specific translations for single-word queries involved enriching our underlying dictionary with gender attributes. Supporting gender-specific translations for longer queries (phrases and sentences) was particularly challenging and involved making significant changes to our translation framework. For these longer queries, we focused initially on Turkish-to-English translation. We developed a three-step approach to solve the problem of providing a masculine and feminine translation in English for a gender-neutral query in Turkish.
Detecting Gender-Neutral Queries
Many Turkish sentences that refer to people are gender-neutral, but not all are. Detecting which queries are eligible for gender-specific translations is a hard problem because Turkish is morphologically complex, meaning that reference to a person can either be explicit with a gender-neutral pronoun (e.g. O, Ona) or implicitly encoded. For example, the sentence “Biliyor mu?” has no explicit gender-neutral pronoun but can be translated as either “Does she know?” or “Does he know?”. This complexity means that we cannot use a simple list of gender-neutral pronouns to detect gender-neutral Turkish queries and need a machine-learned system. We estimate that approximately 10% of Turkish Translate queries are ambiguous, and eligible for both feminine and masculine translations.

To detect these queries, we use state-of-the-art text classification algorithms (same as those used in our Cloud Natural Language API) to build a system that is able to detect when a given Turkish query is gender-neutral. Since this introduces an additional step before obtaining the translations, we had to carefully balance model complexity with latency. We trained our system on thousands of human-rated Turkish examples, where raters were asked to judge whether a given example is gender-neutral or not. Our final classification system is a convolutional neural network that can accurately detect queries which require gender-specific translations.

Generating Gender-Specific Translations
Next, we enhanced our underlying Neural Machine Translation (NMT) system to produce feminine and masculine translations when requested. When no gender is requested, we trained the model to produce the default translation. This involved:
  • Identifying and dividing our parallel training data into those with feminine words, those with masculine and those with ungendered words.
  • Adding an additional input token to the beginning of the sentence to specify the required gender to translate to, similar to how we build multilingual NMT systems:
    • <2MALE> O bir doktor → He is a doctor
    • <2FEMALE> O bir doktor → She is a doctor
  • Training our enhanced NMT model on the feminine, masculine and ungendered data sources. We experimented with various mixing ratios for these sources to enable the model to perform equally well on the three tasks.
If a user's query is determined to be gender-neutral, we add a gender prefix to the translation request. For these requests, our final NMT model can reliably produce feminine and masculine translations 99% of the time. Additionally, the system maintains translation quality on queries without the gender prefix.

Checking for Accuracy
Finally, we have a step that decides whether to display the gender-specific translations. Since the training data that produces the masculine translation is different from the training data that produces the feminine translation, there may be differences between the two translations unrelated to gender. If the gender-specific translations are determined to be low quality, we show only the single default translation. To determine the quality of the gender-specific translations, we verify:
  • If the requested feminine translation is feminine.
  • If the requested masculine translation is masculine.
  • If the feminine and masculine translations are exactly equivalent with the exception of gender-related changes. Even minor changes in the wording between the translations will result in being filtered.
Top: The masculine and feminine translations differ only with respect to gender i.e. “he” and “his” vs “she” and “her”. Hence, we will show gender-specific translations. Bottom: The masculine and feminine translations differ correctly with respect to gender i.e. “he” vs “she”. However, the change from “really” to “actually” is not related to gender. Hence, we will filter gender-specific translations and display the default translation.
Putting it all together, input sentences first go through the classifier, which detects whether they’re eligible for gender-specific translations. If the classifier says “yes”, we send three requests to our enhanced NMT model—a feminine request, a masculine request and an ungendered request. Our final step takes into account all three responses and decides whether to display gender-specific translations or a single default translation. This step is still quite conservative in order to maximize the quality of gender-specific translations shown; hence our overall recall is only around 60%. We plan to increase our coverage and add support for more complex sentences in future iterations.

This is just the first step toward addressing gender bias in machine-translation systems and reiterates Google’s commitment to fairness in machine learning. In the future, we plan to extend gender-specific translations to more languages and to address non-binary gender in translations.

Acknowledgements:
This effort has been successful thanks to the hard work of a lot of people including, but not limited to, the following (in alphabetical order of last name): Lindsey Boran, HyunJeong Choe, Héctor Fernández Alcalde, Orhan Firat, Qin Gao, Rick Genter, Macduff Hughes, Tolga Kayadelen, James Kuczmarski, Tatiana Lando, Liu Liu, Michael Mandl, Nihal Meriç Atilla, Mengmeng Niu, Adnan Ozturel, Emily Pitler, Kathy Ray, John Richardson, Larissa Rinaldi, Alex Rudnick, Apu Shah, Jason Smith, Antonio Stella, Romina Stella, Jana Strnadova, Katrin Tomanek, Barak Turovsky, Dan Schwarz, Shilp Vaishnav, Clayton Watts, Kellie Webster, Colin Young, Pendar Yousefi, Candice Zhang and Min Zhao.

Source: Google AI Blog


Reducing gender bias in Google Translate

Over the course of this year, there’s been an effort across Google to promote fairness and reduce bias in machine learning. Our latest development in this effort addresses gender bias by providing feminine and masculine translations for some gender-neutral words on the Google Translate website.


Google Translate learns from hundreds of millions of already-translated examples from the web. Historically, it has provided only one translation for a query, even if the translation could have either a feminine or masculine form. So when the model produced one translation, it inadvertently replicated gender biases that already existed. For example: it would skew masculine for words like “strong” or “doctor,” and feminine for other words, like “nurse” or “beautiful.”


Now you’ll get both a feminine and masculine translation for a single word—like “surgeon”—when translating from English into French, Italian, Portuguese or Spanish. You’ll also get both translations when translating phrases and sentences from Turkish to English. For example, if you type “o bir doktor” in Turkish, you’ll now get “she is a doctor” and “he is a doctor” as the gender-specific translations.


gender specific translation

Gender-specific translations on the Google Translate website.

In the future, we plan to extend gender-specific translations to more languages, launch on other Translate surfaces like our iOS and Android apps, and address gender bias in features like query auto-complete. And we're already thinking about how to address non-binary gender in translations, though it’s not part of this initial launch.


To check out gender-specific translations, visit the Google Translate website, and you can get more information on our Google Translate Help Center page.

Source: Translate


A new look for Google Translate on the web

It’s been twelve years since the launch of Google Translate, and since then Translate has evolved to keep up with the ways people use it. Initially translating between English and Arabic only, we now translate 30 trillion sentences per year across 103 languages.

Google Translate has become an essential tool for communicating across languages, and we recently redesigned the Translate website to make it easier to use. Here’s what you need to know:

  • The site’s new look is now consistent with other Google products, and updated labeling and typography make it easier to navigate. For instance, you’ve always been able to upload documents for translation, but now that feature is easier to find. 
  • Now it’s even more convenient to save and organize important translations you regularly utilize or search for. We’ve added labels to each saved translation, so if you speak multiple languages, you can sort and group your translations with a single click.
  • We've made the website responsive so it can adjust dynamically for your screen size. So when we launch new features, you get a great web experience across all your devices: mobile, tablet, or desktop. 
translate web redesign gif

The new responsive website adjusts dynamically to your screen size.

To check out the new site, visit translate.google.com.

Source: Translate


Bringing hope to a refugee family, using Google Translate

In 2015, I joined Google to be a part of a company using technology to help others. I’m proud that Google’s commitment to its mission—to organize the world’s information and make it universally accessible and useful—remains strong 20 years in. I knew I wanted to be a part of it all, but had no idea that I would experience the power of our mission firsthand, and that it would help me to forge a friendship when I least expected it.

For the past three years, my wife and I have been working with organizations involved with refugee resettlement efforts. We both have immigrant parents, so we’ve heard stories about resettling in a country to make a better life for your children, but being forced to leave a country is very different. These refugees are often fleeing from life threatening situations. Aside from dealing with their past trauma and being in an unfamiliar place without a support system, they often can’t speak the local language.

My wife and I learned of a family of four—Nour, Mariam, three-year old Sanah and six-month-old Yousuf—who settled in Rialto, 45 minutes from where my wife and I grew up in Southern California. Through the assistance of organizations such as Hearts of Mercy and Miry’s List, they settled into an apartment shortly before giving birth to Yousuf. Still recovering from injuries sustained in Syria, Nour was unable to work, and had to rely on the help of others to get by. Without a car, their options were further limited. Then, in April of this year, they faced their hardest challenge yet: their daughter Sanah was diagnosed with Stage 4 Neuroblastoma.

We wanted to help, but didn’t know where to start—and as new parents ourselves, we could relate on a personal level. We fundraised for the family and collected toys for Yousuf and Sanah in hopes that they could feel supported. Moreso, we wanted to help them get through Sanah’s treatments with as little to worry about as possible.

A few weeks after we first heard of their story, we went to their home to meet in person. Nour was waiting outside for us, and we quickly realized there was a challenge that we had overlooked: the family only spoke Arabic. There I was, face to face with Nour, wanting to hear his story and reassure him that he’s surrounded by a supportive community, but couldn't convey those thoughts or give Nour the ability to convey his. The only option I could think of was Google Translate, which I had used in previous international trips, and hoped would bridge this gap.

I opened the app to translate a few words, but we couldn’t get far by manually typing sentences. Instead, I tried "conversation" mode, which allows for real-time audio translations and makes the interaction feel more natural. We talked about his family’s story and what they were up against. I learned that back in Syria, Nour was shot twice in the back, and endured the deaths of his brothers. Now, Nour and Mariam are giving up everything to take care of Sanah and spend up to two hours commuting on a bus to and from her hospital treatments. Through all of this, they continue to be optimistic and hopeful, and are grateful for being able to make it to America.

image (2).png

A snapshot of my visit with Nour.

I never imagined that we could sustain a 90-minute conversation in two languages, and that it would bring us closer together, inspiring me in a way I didn’t expect. Without Translate, we would have exchanged a few pleasantries, shared poorly communicated words and parted ways. Instead, we walked away with a bond built on an understanding of one another—we were just two fathers, talking about our fears and hopes for our family’s future. To this day, we stay connected on how the family is doing, and I’m looking forward to keeping this relationship going for a long time.

Refugee families often find themselves in situations that may seem normal to you and me—like at the DMV trying to get a driver’s license—or worse, in a dire situation like a hospital, with no way of communicating. We generally think of technology as an enabler of change, driving efficiency or making the impossible happen. But in this case, technology allowed me to make a life-changing connection, and brought me closer to family who was very far away from home.

Source: Translate


Tune in for the world’s first Google Translate music tour

Eleven years ago, Google Translate was created to break down language barriers. Since then, it has enabled billions of people and businesses all over the world to talk, connect and understand each other in new ways.

And we’re still re-imagining how it can be used—most recently, with music. The music industry in Sweden is one of the world's most successful exporters of hit music in English—with artists such Abba, The Cardigans and Avicii originating from the country. But there are still many talented Swedish artists who may not get the recognition or success they deserve except for in a small country up in the north.

This sparked an idea: might it be possible to use Google Translate with the sole purpose of breaking a Swedish band internationally?

Today, we’re presenting Translate Tour, in which up and coming Swedish indie pop group Vita Bergen will be using Google Translate to perform their new single “Tänd Ljusen” in three different languages—English, Spanish and French—on the streets of three different European cities. In just a couple of days, the band will set off to London, Paris and Madrid to sing their locally adapted songs in front of the eyes of the public—with the aim of spreading Swedish music culture and inviting people all over the world to tune into the band’s cross-European indie pop music.

Translate Tour 2_Credit Anton Olin.jpg

William Hellström from Vita Bergen will be performing his song in English, Spanish and French.

Last year Google Translate switched from phrase-based translation to Google Neural Machine Translation, which means that the tool now translates whole sentences at a time, rather than just piece by piece. It uses this broader context to figure out the most relevant translation, which it then rearranges and adjusts to be more like a human speaking with proper grammar.

Using this updated version of Google Translate, the English, Spanish and French translations of the song were close to flawless. The translations will also continue to improve, as the system learns from the more people using it.

Tune in to Vita Bergen’s release event, live streamed on YouTube today at 5:00 p.m. CEST, or listen to the songs in Swedish (“Tänd Ljusen”), English (“Light the Lights”), Spanish (“Enciende las Luces”) and French (“Allumez les Lumières”).

Source: Translate


Making Google Translate better—and more magical—for seven Indian languages

As the novelist and physician Khaled Hosseini wrote “if culture was a house, then language was the key to the front door, to all the rooms inside”. We agree—language is incredibly important, not only for understanding culture, but also for accessing information in general. That’s why over the past several months, we’ve been updating our products to work better for the many Indian language users coming online every day. In April, we launched several new features and updates, including neural machine translation for more languages, and just a few weeks ago we enabled voice input for additional eight Indian languages. Today, we’re bringing several updates to the Google Translate app, making it easier for speakers of Bengali, Gujarati, Kannada, Marathi, Tamil, Telugu, and Urdu to translate when they’re on the go. Now, you can do offline translations and instant visual translation in seven more Indian languages, type a Translate query with your voice in eight more languages (the seven above and Malayalam), and use conversation mode in two more languages: Bengali and Tamil. All these features have been available in Hindi, and are now accessible for more languages on both Android and iOS*.



Offline Translation in seven more Indian languages
With Google Translate, you can easily turn your phone into a powerful translation tool––for studies, business, or travel. But whether you’re on a spotty connection in a remote area or just want to switch off data while you’re on the go, sometimes you’d like to translate a word or sentence even when you’re not connected to the internet. This rings particularly true for us here in India, where connectivity can be an issue. To help you translate in moments like this, we’ve already enabled Offline Translation in Hindi, and now we’re launching the feature for seven more Indian languages––something many Indian users have asked about.


If you’d like to do offline translations in say Kannada, you can download the Kannada language pack when you’re on WiFi. Then just open the Translate app, select Kannada on either side of the screen and then tap the download button. English is automatically embedded in all language packs, so you can start translating offline between English and your language straight away.
Instantly translate signs or menus with Word Lens––now in more Indian languages
With today’s update, we’re also launching instant visual translation for these seven Indian languages, so you can now translate signs or menus from English to Bengali, Gujarati, Kannada, Marathi, Tamil, Telugu, and Urdu, in addition to Hindi. The Translate app already lets you use camera mode to snap a photo of English text and get a translation for it in these languages. Now, we’re taking it to the next level and letting you instantly translate text using your camera—so it’s way easier for speakers of local Indian languages to understand English street signs in the city, or decide what to order from a restaurant menu. Word Lens is powered by machine learning, using computer vision to distinguish between letters on an image.


To get started, open the Translate app, point your camera at an English sign or text, and you’ll see the translated text in your language overlaid on your screen. If you’re using Word Lens in a language for the first time, you might be prompted to download a translation file first, as Word Lens works offline.







Start a bilingual conversation in Bengali or Tamil (and Hindi)
Conversation mode is a feature that lets you have a bilingual conversation with someone, simply by talking to the Google Translate app. For instance, when you’re at a marketplace trying to snag a good deal on that shawl, Conversation Mode can help you converse with the locals. This already works for Hindi, and today we’re launching two additional languages: Bengali and Tamil. Simply tap the mic to start speaking in a selected language, then tap the mic again, and the Google Translate app will automatically recognize which of the two languages are being spoken, letting you have a fluid conversation—it’s like having an interpreter in your pocket!



Translate with your voice in nine Indian languages
Typing in Indian languages on a phone can be slow and cumbersome, in fact more people in India are using their voice to “type” a translation query than the keyboard. That’s why we’re excited to bring Voice Translation to more Indians––with the recent launch of voice input for eight additional languages, speakers of Hindi and now Bengali, Gujarati, Kannada, Malayalam, Marathi, Tamil, Telugu, Urdu, and Tamil can dictate their translation queries using their voice.  For instance, if you’re on the go and would like to type with your voice in Urdu, open the Translate app, select Urdu on the left side of the screen, and tap the microphone to start talking.


We’re hoping these new features help further bring down language barriers and provide more Indians with the ability to access information around them. All features announced today are already available in Hindi on the Google Translate app, and have started to roll out in the additional Indian languages both on Android and iOS*. With these updates, the Google Translate app supports Offline Translation for 59 languages, Word Lens for 37, Voice Translation for 66, and conversation mode for 40 languages. Our goal is to bring these and other features to more and more languages, breaking down language barriers in India and countries around the world.


*Please note that Voice Translation for the eight additional Indian languages currently only works on Android, but we’re looking to roll it out on iOS soon


Posted by Barak Turovsky, Product Lead, Google Translate

Making the internet more inclusive in India

More than 400 million people in India use the internet, and more are coming online every day. But the vast majority of India’s online content is in English, which only 20 percent of the country’s population speaks—meaning most Indians have a hard time finding content and services in their language.

Building for everyone means first and foremost making things work in the languages people speak. That’s why we’ve now brought our new neural machine translation technology to translations between English and nine widely used Indian languages—Hindi, Bengali, Marathi, Gujarati, Punjabi, Tamil, Telugu, Malayalam and Kannada.

Neural machine translation translates full sentences at a time, instead of pieces of a sentence, using this broader context to help it figure out the most relevant translation. The result is higher-quality, more human sounding translations.

Just like it’s easier to learn a language when you already know a related language, our neural technology speaks each language better when it learns several at a time. For example, we have a whole lot more sample data for Hindi than its relatives Marathi and Bengali, but when we train them all together, the translations for all improve more than if we’d trained each individually.

NMT Translation India.jpg
Left: Phrase-based translation; right: neural machine translation

These improvements to Google Translate in India join several other updates we announced at an event in New Delhi today, including neutral machine translation in Chrome and bringing the Rajpal & Sons Hindi dictionary online so it’s easier for Hindi speakers to find word meanings right in search results. All these improvements help make the web more useful for hundreds of millions of Indians, and bring them closer to benefiting from the full value of the internet.

Source: Translate


Making the internet more inclusive in India

More than 400 million people in India use the internet, and more are coming online every day. But the vast majority of India’s online content is in English, which only 20 percent of the country’s population speaks—meaning most Indians have a hard time finding content and services in their language.

Building for everyone means first and foremost making things work in the languages people speak. That’s why we’ve now brought our new neural machine translation technology to translations between English and nine widely used Indian languages—Hindi, Bengali, Marathi, Gujarati, Punjabi, Tamil, Telugu, Malayalam and Kannada.

Neural machine translation translates full sentences at a time, instead of pieces of a sentence, using this broader context to help it figure out the most relevant translation. The result is higher-quality, more human sounding translations.

Just like it’s easier to learn a language when you already know a related language, our neural technology speaks each language better when it learns several at a time. For example, we have a whole lot more sample data for Hindi than its relatives Marathi and Bengali, but when we train them all together, the translations for all improve more than if we’d trained each individually.

NMT Translation India.jpg
Left: Phrase-based translation; right: neural machine translation

These improvements to Google Translate in India join several other updates we announced at an event in New Delhi today, including neutral machine translation in Chrome and bringing the Rajpal & Sons Hindi dictionary online so it’s easier for Hindi speakers to find word meanings right in search results. All these improvements help make the web more useful for hundreds of millions of Indians, and bring them closer to benefiting from the full value of the internet.

Source: Translate