When it comes to languages, many problems arise in typical translation services. Either it is bad grammar or the translation does not completely make sense afterward. It is essential that these mistakes do not fall through during the final translation, whether it's during a business transaction or simply a conversation. Luckily, technology has advanced this process with the help of automation and artificial intelligence, assisting with speed and accuracy. In this article, we will discuss some of the most prominent and up-and-coming companies that provide these automated solutions that break down the language barrier.

Over the last few years, online education platforms have seen an increase in adoption of and an uptick in demand for video-based learnings because it offers an effective medium to engage learners. To expand to international markets and address a culturally and linguistically diverse population, businesses are also looking at diversifying their learning offerings by localizing content into multiple languages. These businesses are looking for reliable and cost-effective ways to solve their localization use cases. Localizing content mainly includes translating original voices into new languages and adding visual aids such as subtitles. Traditionally, this process is cost-prohibitive, manual, and takes a lot of time, including working with localization specialists.

Imagine a surgeon taking video calls with patients across the globe without the need of a human translator. What if a fledgling startup could easily expand their product across borders and into new geographical markets by offering fluid, accurate, multilingual customer support and sales, all without the need of a live human translator? What happens to your business when you're no longer bound by language? It's common today to have virtual meetings with international teams and customers that speak many different languages. Whether they're internal or external meetings, meaning often gets lost in complex discussions and you may encounter language barriers that prevent you from being as effective as you could be.

Amazon Translate is a neural machine translation service that delivers fast, high-quality, affordable, and customizable language translation. Amazon Translate now supports formality customization. This feature allows you to customize the level of formality in your translation output. At the time of writing, the formality customization feature is available for six target languages: French, German, Hindi, Italian, Japanese, and Spanish. You can customize the formality of your translated output to suit your communication needs.

Amazon Translate is a neural machine translation service that delivers fast, high-quality, affordable, and customizable language translation. This post shows how you can mask profane words and phrases with a grawlix string ("?$#@$"). Amazon Translate typically chooses clean words for your translation output. But in some situations, you want to prevent words that are commonly considered as profane terms from appearing in the translated output. For example, when you're translating video captions or subtitle content, or enabling in-game chat, and you want the translated content to be age appropriate and clear of any profanity, Amazon Translate allows you to mask the profane words and phrases using the profanity masking setting.

Web browsers can be a single pane of glass for organizations to interact with their information--all of the tools can be viewed and accessed on one screen so that users don't have to switch between applications and interfaces. For example, a customer call center might have several different applications to see customer reviews, social media feeds, and customer data. Each one of these applications are interacted with through web browsers. If the information is in a language that the user doesn't speak, however, a separate application often needs to be pulled up to translate text. Web browser plugins enable customization of this user experience.

What is Amazon Web Services? Amazon Web Services or AWS is world's broadly adopted cloud platform . AWS provides with a number of useful cloud computing services that are very much reliable, scalable and cost efficient as they say. AWS provides services like storage, networking, remote computing, servers, email, mobile development and security . So now coming to Amazon machine learning, frankly means leveraging ML algorithms on cloud platforms like AWS .

This post is co-authored by Lezgin Bakircioglu, Innovation and Security Manager at Daniel Wellington. In their own words, "Daniel Wellington (DW) is a Swedish fashion brand founded in 2011. Since its inception, it has sold over 11 million watches and established itself as one of the fastest-growing and most coveted brands in the industry." In this post, we share how DW saved 99% on translation costs with Amazon Translate and other AWS services. At DW, having the ability to respond to customers in their local language is critical to the customer journey.

In our previous post, we described how to translate documents using the real-time translation API from Amazon Translate and AWS Lambda. However, this method may not work for files that are too large. They may take too much time, triggering the 15-minute timeout limit of Lambda functions. One can use batch API, but this is available only in seven AWS Regions (as of this blog's publication). To enable translation of large files in regions where Batch Translation is not supported, we created the following solution.

When translating the English phrase "How are you?" to Spanish, would you prefer to use "¿Cómo estás?" or "¿Cómo está usted?" instead? Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Today, we're excited to introduce Active Custom Translation (ACT), a feature that gives you more control over your machine translation output. You can now influence what machine translation output you would like to get between "¿Cómo estás?" or "¿Cómo está usted?". To make ACT work, simply provide your translation examples in TMX, TSV, or CSV format to create parallel data (PD), and Amazon Translate uses your PD along with your batch translation job to customize the translation output at runtime.