Language translation technology Archives - Into23

What is NLG and how does it work with the Natural Language Process (NLP)?

NLG is a type of AI and language translation technology that is becoming more prominent in business platforms.

NLG standards for Natural Language Generation and it is changing the way we interact with machines and the way businesses gather data. What is NLG exactly, and what makes it different from other technologies? With the compound annual growth rate of the NLG market expected to reach 1.6 billion dollars by 2027, you need to know about NLG.

What is NLG?

Chatbot

A chatbot, which is often used for FAQ portions of websites and customer support, is one type of NLG. – Photo by mohamed_hassan on Pixabay

NLG is a type of AI that automatically processes data into sentences and stories, in either written or narrative form, in a way that’s easy for us humans to understand. The NLG can take massive amounts of data from pre-set templates to form a sentence, reply, or inquiry that reads like a natural human conversation. This data and our inputted responses to this data create and add to a database of information that businesses and researchers can use to improve a process or product. 

When is NLG used?

Alexa

Any time you beckon Alexa or Siri, an NLG has been used to create that product and experience – Photo by Anete Lusina from Pexels

NLG is being used for a vast array of applications, and chances are that you’re already encountering and engaging with this technology daily. Here are a few broad ways that both businesses and consumers use NLG,

  • Chatbots or conversational AI assistants – Used on websites and business platforms to automatically answer customer inquiries. The advanced use of NLG carries a two-way conversation and responds to verbal commands. Examples are platforms Alexa, Siri, Google Assistant and Cortana. 
  • Machine translation tools – Tools that translate one language to another, such as Google Translate.
  • AI blog writers – Used for content creation. The NLG uses one language model and data set to write sentences and full-length articles. 
  • Analytics – The NLG is created to detail insights from business data and reports, such as financial reports and spreadsheets and put it all into a format or narrative that’s easy to understand for businesses and their customers. 
  • Automated leading emails and messages – This NLG creates predictive text for users when writing in emails and messaging platforms. 
  • AI transcription tools – With speech recognition, the NLG takes audio and turns it into text.
  • Semantic analysis A platform used to determine what language best resonates and reaches a specific audience of which the NLG is used to create messages to which the customer is likely to respond.  

NLG has become one of the translation solutions used by global businesses as part of their website localization, eLearning translation and more. NLG is used as part of the machine translation post-editing process used by international translation companies and translation agencies online

How the Natural Language Process (NLP) works

Computer AI

NLP is a series of Ais that work in a relationship with a user to create and exchange of information that benefits the user and the business.. – Photo by geralt on Pixabay

 

NLP is a blanket term that refers to NLG and Natural Language Understanding (NLU). NLP is a framework that converts unstructured data to structured data. NLU is the ability of a machine to use syntactic and semantic analysis to gather meaning from a piece of text or speech. It is the NLG that allows devices to create content from the NLU data content. In short, NLU lets a computer understand what data the user is giving it. At the same time, NLG provides data back to the user from the computer in a way the user can understand, thus the Natural Language Process.

Making an NLG requires several steps and a substantial amount of NLU data to create content that resonates and sounds natural. Whether it’s a chatbot or a machine translation tool, these are some of the steps and considerations that go into making an NLG,

  • Content analysis – This step analyses data to identify the main topics that should be included and what the result of the process is expected to be.  
  • Data interpretation – As patterns are identified, they are put into context for machine learning.
  • Document structure and sentence aggregation A document is created along with a narrative structure with the interpreted data. From there, relevant sentences are isolated and combined to depict the topic accurately. 
  • Grammar – Grammar rules, along with the syntactical structure of the source language, are added to ensure that the text sounds natural.
  • Final output – The final output is presented in a template or format of the programmer’s selection. Such as a message from a chatbot, a piece of the translated text, an audio reply for personal assistant devices etc. 

The Future of NLG

Woman on phone transit

NLG is used in a variety of apps and processes on our phones. – Photo by Ketut Subiyanto from Pexels

NLG has created ways for businesses to communicate data efficiently and effectively, which increases productivity and reduces business costs. It presents data and information in an accessible manner while collecting big data that will lead to specific insights into a business. NLG has been used in different business industries, from insurance, retail, finance, media, eLearning platforms, eCommerce and eCommerce translation, manufacturing, translation management and more. 

While technology has come a long way, NLG is still limited compared to real human writing and semantics. NLG can only act on the NLU data, which, currently, doesn’t stack up to the ingenuity of human writing and content, which makes the quality of NLG content one of its biggest weak points. NLG, however, is not without its merit as the NLP is superb at generating human insights from big data, especially at a volume that we, as humans, are not capable of producing. As NLG can be used in various markets, it is a valuable tool that can be used in many ways for any business. Take translation and localization, for example.

For businesses that want translation and localization services to expand into other global markets, NLG is an important part of a quality translation. Translators use machines to help expedite the translation process and fine-tune it with their human expertise. This process is called machine translation post-editing.

Related: Machine, mind, or machine and mind: how to best deploy today’s machine translation solutions

Into23 provides translation management and translation solutions that cater to your business. Into23 can help you use an NLG in multiple languages for your business; whether it’s a customer support chatbot or transcription services for a voice assistant, Into23 can help your customers interact with your business better.

Top 6 emerging translation trends of 2022

What types of marketing translation trends are becoming prominent in 2022? Here’s what to expect for the remainder of the year.

Content translation services have seen a massive increase in demand, with much of this growth being linked to the internet, the pandemic, our global expansion and uses of technology. The market worth of this industry has grown and is looking to grow further in 2022 as the pandemic has slowly stabilised and more people and places of business took their work and education online and have kept it there. 

What has driven growth in the translation industry in 2022?

Man in pjs

The pandemic saw more people working from home and increased online spending. – Photo by Thirdman

The biggest driver behind the growth of the translation industry has been the increased need for people to access information in different languages and cultures, coinciding with the growth of technology and our reliance on it. Technology has made it possible for people to communicate in meaningful ways across the globe in various formats and languages, which became increasingly important during the pandemic. Language translation technology has also come a long way, making it faster and more accessible for people and businesses to get what they need.

While translation solutions come in many forms, depending on your business or need, these areas are some of the most noticeable upward trends of 2022. They are relevant aspects to consider if you’re looking to expand globally. 

Multilingual customer support

Chatbot

Trends show that people prefer to contact companies via messaging apps when looking for support. – Photo by mohamed_hassan

If you have a platform that has been localized for customers, you’ll also need multilingual customer service support. As more people use their phones for everyday tasks, from emails to banking, these services must be provided and serviced in the customer’s language. The same goes for customer support. Today, 67% of consumers expect to be able to message or chat with a business when they need support. As this number is likely to increase, businesses that want to continue to reach their customers globally must consider multilingual customer support in their localization strategies. A marketing translation agency can provide support and resources in multiple languages to help fortify an existing localization strategy or start a new one. 

Increased use of machine translation post-editing

Machine translation has become an essential part of the translation industry and is a trend that has continued upward for several years. 

What is machine translation post-editing?

Machine translation is when you enter content into an automated software translation tool, and the machine converts it into the target language. Google translate is the most well-known machine translator that most of us use in our daily lives. However, the results of these machine translations alone vary drastically in terms of accuracy and are not sufficient enough to be used in business for a variety of reasons.

Related: Why Google translate isn’t effective enough for business

The post-editing portion comes after the machine translation. A professional translator will go over the machine translation and compare it to the original text to get the most accurate translation. Machine translation post-editing is desirable for businesses and marketing translation as it offers a quick turnaround at a lower cost.  

The machine translation market has been steadily increasing and is anticipated to reach 230.67 million USD by 2026. 

Increase usage of eLearning platforms

Woman wearing a mask

The pandemic changed our lives, but one of the largest impacts was felt in the education sector. – Photo by Edward Jenner

The pandemic may have kept us at home the last few years, but eLearning platforms kept us learning and connected. Forbes estimates that by 2025, the eLearning sector could be worth as much as USD 355 billion dollars. As the business and education sectors looked towards online learning tools and software to maintain a global reach, the videos, courses and quizzes also needed to be updated and translated for global audiences. This newfound flexibility offers benefits to businesses, educators and students as people can work and learn on their own time from the comfort of a home or café. eLearning and eLearning translation shows no signs of slowing and will continue to increase in demand as more and more people and businesses maintain a work/study from home approach. 

Businesses using media localization

Two different types of media are trending right now, podcasts and videos. Podcasts are now being used for business, pleasure, and education and have seen a large rise in listeners, especially considering they’ve only been around for two decades. It is estimated that there will be around 424.2 million podcast listeners worldwide in 2022 and that podcasts will be a USD 94.88 billion industry by 2028.

Videos are also an essential part of today’s media market. In 2019 alone, the average person’s video consumption was 84 minutes daily. Enter the pandemic, and by 2021 that average was nearly 100 minutes per day. Now we’re in the beginning part of 2022, and video streaming and downloads are anticipated to account for 82% of the global internet traffic. A study done by Wyzowl found that 81% of businesses now create at least some video content. Point of fact, if you’re not using videos in your business marketing materials, you should be. 

With the impressive rise of both video and podcast consumption, the need for localization, such as audio transcription services, multilingual voice-over services, or subtitling services, becomes necessary for going global and is a trend that will continue well past 2022. 

Subtitles have become a must

As previously mentioned, videos are currently making up the majority of consumer internet traffic. To make business ads, videos, and video courses more accessible for everyone, subtitles have become essential. 

Even outside of any language or subtitle translation, many of the videos people consume on social media are often viewed on mute, meaning that if a video doesn’t have subtitles, it’s more likely to be skipped and scrolled past. Subtitles have become a required feature for views and impressions, even when the language hasn’t been changed.  

Further, if you do require language translation for a video to reach new audiences, subtitling is generally more affordable than dubbing and is just as effective in reaching your target audiences. 

Multilingual SEO strategies 

By now, it’s obvious that the biggest trend is the translation and localization of businesses in general. This is an upward trend that was growing even before the pandemic. Going global means having an online presence and reaching and connecting to audiences in new and meaningful ways with technology. While website localization is becoming more common, it is often an afterthought. Businesses are now opting to create a multilingual SEO strategy from the get-go so that their business content and practices are aligned with their global goals from the start.

What is a multilingual SEO strategy?

It is the practice of optimizing your SEO in more than one language. This includes everything from websites, eCommerce platforms, video content, social media, customer support and more. The best way to develop a multilingual SEO strategy is to work with a translation project management company that offers multilingual translation services and marketing translations. This ensures an effective strategy that is aimed at a specific target audience and ensures effective use of your business’s resources along with a quality translation that showcases the values and goals of your business. 

Into23 offers quality translation solutions for all major global languages to help your business enter any global market. Bring your business into 2022 and beyond with our transparent and quality language solutions. Contact us today for a free quote to start your global journey.

The language of food and farming: Agribusiness Translation in 2022

The global Agribusiness sector has been reshaped by the impact of the pandemic. Agriculture in developing and emerging economies has faced extensive setbacks due to supply chain disruptions and the disproportionate effect that COVID 19 has had on populations in the world’s major production regions. The industry has had to adapt with a combination of support programs for smallholder farmers and increasing investment in agritech, a major agribusiness trend in recent years. 

Set up your investment in agricultural machinery with multilingual translation services

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Agritech involves improving the efficiency of industrial equipment like tractors and processing machines on the one hand, while developing completely new technologies, platforms and applications on the other. A report from the World Government Summit identifies new production techniques, supply chain innovations and cross-industry applications as three major agribusiness trends in 2021.

Hydroponics, bioplastics and desert agriculture revolutionize the way agricultural products are grown, while vertical farming, genetic engineering and 3D printing enable expanded production in urban environments. Blockchains provide enhanced logistics solutions that streamline and digitise agribusiness finance, while data analytics provide actionable insights on both the production and distribution side. IoT integration brings agricultural machinery online and closely integrates every step of production, which is increasingly automated with digital agriculture applications of robotics, which enhance soil monitoring and provide a chemical free pest control solution.

Agribusiness enterprises have to adapt to the current landscape by adjusting their production strategy in order to maintain competitive advantage and ensure sustainable development. Adopting new platforms and adapting to digital agriculture brings an additional layer of challenge that may be overlooked: expert translation services for agriculture.

Translation Management as a Service for Agribusiness

expert translation services for agriculture

The global agribusiness industry is complex, and digital agriculture makes it even more so. In addition to the inherent requirement to provide user interfaces and documentation in multiple languages, Agriculture involves different standards procedures and regulation in every country. Terminology is a key consideration that requires not only a solid understanding of the industry, but also an appreciation of the vital importance of consistency across international operations.

Agribusiness enterprises require expert technical document translation services in order to ensure that crucial context is accounted for, while the sheer scale of operations makes Translation Management as a Service (TMaaS) a necessity. The complexity of the challenge scales with level of data generated by digital agriculture technology. In agribusiness, the volume of information flowing in multiple directions in real time requires companies to plan ahead to adapt.

For example, digital agriculture initiatives in China have accelerated the rollout of 5G networks in rural areas. Automated systems can track crop and livestock health, monitor yields, and assess landscape fertility with satellite imagery. The level of information this generates requires a comprehensive solution to efficiently track and translate, while user interfaces have to be understood by field operators who require training and administrative staff who need to fully understand the information to file reports. Multinational agribusiness enterprises have to ensure that the entire information and communication loop runs seamlessly at all times.

Innovative platforms and connected equipment provide the level of the precision required to effectively manage an agribusiness value chain. Translating this information requires the same standard of accuracy, with a steady stream of information to continuously maintain. With Translation Management as a Service, agricultural enterprises can centralize and coordinate their terminology, translation memory and document versions with a cloud-based translation system.

Agribusiness enterprises also face the challenge of coordinating translations for their fertilizer products, which includes packaging, brochures, legal documents and training manuals. Into23’s translation management system identifies key phrases that provide a basis for subsequent translation requirements. With our language translation technology, higher the volume, the faster we can translate at reduced cost.

Translators who understand Agriculture

expert translation services for agriculture

Our technical document translators are experienced with agricultural equipment and agri-input literature and understand how to handle the volume and attention to detail required in business translation services. The document translation team works from an enterprise model perspective and plans for scalability ahead of time. They are also adept with the language and vocabulary of agribusiness, and fully understand the difference between conventional usage and industry context.

From livestock nutrition to pest control, plant breeding, fertilizers and crop protection, we work with the level of accuracy required in any language-pair. Whether it’s Polish to Chinese, Portuguese to Chinese, Urdu to Chinese, Chinese to Hindi, or more conventional language pairs like German to French, we understand application, context and culture.

Agribusiness enterprises frequently need to coordinate operations in Africa, South Asia, Southeast Asia, and China. Equipment is often manufactured in the PRC, while seed and soil solutions are developed in Europe and deployed in Africa. The EU is a major market for processed agri-commodities while Hong Kong and Singapore serve as important business hubs for the sector. 

Into23 is an expert enterprise translation service provider based in Hong Kong, and we provide a comprehensive solution for agribusiness operations. We can coordinate and plan projects that require multiple language pair translations at scale for different aspects of the operations cycle, including sourcing, production, marketing, sales, logistics and compliance. 

It is important to work with an agency that not only appreciates the importance of accuracy but also understands how to coordinate documentation translations at scale for a multinational enterprise. Working with multiple translation agencies often results in disjointed datasets and an unacceptable level of variability in critical communications. Labeling and leaflet vocabulary should seamlessly link across operations, regions and locations.

The advent of digital agriculture accelerates the pace at which agribusiness information and communications will flow. In 2022, we are only in the initial the beginning of the fourth industrial revolution, but the momentum is unmistakable.

At Into23, we are passionate about business, languages and cultures. Our linguists are keen to assist any enterprise that wants to proactively face the challenge of adaptation. From experience, we understand how to coordinate enterprise projects at scale and ensure smooth transitions, which gives us a decisive advantage with supporting agribusiness with multilingual translation services over the upcoming decade.

Feel free to get in touch or share your thoughts on global agriculture and cross-cultural collaboration. We value the stories our clients want to share, because as translators, we understand that people bring vibrance and vitality to businesses.

Machine, mind, or machine and mind: how to best deploy today’s machine translation solutions

Advances in machine translation (MT) mean enterprises now have a sophisticated translation solution in their toolkit that can translate quickly and at scale. Long gone are the days of weird menu translations and Yoda-like results. But given the recent rapid advancements in artificial intelligence and machine learning, companies must navigate how to optimally deploy this productivity-boosting approach alongside human translation. Knowing where and when to use machine translation will ensure translations are cost-effective and fit for purpose. Embracing translation technology and innovation in the right areas is the way to increase engagement and efficiency. Read on to find out the criteria you need to consider when deploying the latest machine translation solutions.

From little acorns

Though you may think language translation technology is a relatively modern phenomenon – after all, computers have only been around since The Babbage Difference Engine back in 1822 – its roots stretch back, all the way to the Arabian peninsula in the 9th century, where one al-Kindi translated ancient Greek mathematics, science and philosophy texts that had been lost to European civilisation, helping spark the Renaissance in the process. He developed various systems based on frequency analysis and statistics, key concepts in MT. Now, AI translation software enables clients to customise according to subject area, such as meteorological reports. This has massively widened MT’s applicability and usefulness.

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Where is machine translation now?

Machine translation was initially developed in the 1950s, and has since been transformed through continuous advances, diverging into four categories: SMT, NMT, RBMT, and Hybrid Machine Translation. SMT, or statistical machine translation, automatically maps sentences in one language into another, whereas NMT, or Neural Machine Translation, encompasses a neural network that relies on algorithms working together to process highly complex data inputs. RBMT, or Recurrent Batch Machine Translation, replaces the input texts with translations of a set of translations of the same text, and Hybrid Machine Translation combines elements of both NMT and RBMT.

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Key benefits

The advantages of using machine translation mean it is a very effective and efficient solution in a company’s toolkit. Firstly, machine translation is incredibly fast. It can process huge volumes of text in a near instant. Therefore, it improves efficiency and productivity. Companies that deploy machine translation typically see an improved profit margin, all else being equal. Secondly MT is scalable. If you need to translate a short document or an entire library’s worth of text, MT can handle it. Lastly, and partly as a result of the first two points, machine translation is much more cost-effective than human translation. Before you rush out to onboard a range of machine translation solutions, there are many circumstances where human translation is preferable, and numerous others where a hybrid approach of machine translations processed by human editors is best.

How best to deploy machine translation

Getting the best out of machine translation requires optimally deploying it. Several factors will determine the ideal approach. A Nimdzi survey of 33 localisation buyers found 22.6% report extensively using neural machine translation. The survey notes that sectors like media, video gaming and marketing are laggards in MT adoption, mainly because they require high levels of cultural sensitivity and creativity that MT as of today can’t match. That’s not to say MT isn’t making inroads into these areas. For example, world top-10 gaming company Electronic Arts (EA) adopted MT tech quite early in its development. Notably, in areas where content is intended to prompt emotional engagement, EA uses human-edited MT translations. The survey also found that in circumstances that directly impact business revenue, human translation is preferred.

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Applying those findings to business activity, MT is useful for quickly transmitting a message to large numbers of people in various locations. Even in this instance, it’s always wise to have a human check the copy. The content lifecycle is also a consideration. For short-lived content, such as product specs on a short run of merchandise, then the return on investment is not there for human translation, which costs more than MT. Here, the requirements for quality and timeliness are key determinants.

Another great use case for MT is where recipients are aware that the content they are consuming is translated by a machine. This enables them to read with caution.

To summarise, the important parameters to consider are:

  • Scale: If you are translating small amounts of text occasionally, then off-the-shelf MT is suitable. If the volume is any higher than that, hybrid translation often is most suitable.
  • Timeframe: A very short turnaround time is where MT excels. However, be mindful that the quality might not be sufficient.
  • Content consumers: One of the golden rules of translation is to pitch to your audience. Consider whether MT will meet your audience’s needs. If your target audience just needs to get the general gist of a text, then MT will suffice. However, if expectations around quality are higher, then human translation or human-edited machine translation is the optional approach.
  • Objective: The goal of the translation must be carefully considered. For example, if you wish to sign a legally binding contract and need to translate it for the other party to sign, then accuracy is paramount when it comes to legal document translation. Another example is scientific and technical translation, which would require a custom language translator.

A bright future

In a sign of just how far MT could go in the future, a group of scientists recently launched a project to decode sperm whale ‘speech’ with a view to enabling whale-human communication. That would be an interesting one to add to the digital translation services already available. The Cetacean Translation Initiative is using AI to understand whales’ clicking sounds, known as codas. The scientists are deploying natural-language processing, which processes spoken and written communication, to that end.

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MT is improving all the time, and as it does, it becomes applicable to an ever-expanding set of scenarios. However, we aren’t anywhere near the point where MT is good enough for businesses to abandon Machine Translation Post-Editing (MTPE). Finding the right balance is key, and a professional translation agency will help you navigate the optimal configuration of MT, human translation and MTPE. Get in touch today to speak to an expert and explore your options.