Machine translation breaks down language barriers and helps understand content in various languages. This technology has transformed global communication, facilitating connections, collaborations, and mutual understanding worldwide.
But caution is necessary when using machine translation for critical or professional tasks that require absolute accuracy and cultural sensitivity. Machine translation has been a long-standing goal in computer science, and recent advances in natural language processing, artificial intelligence, and computing power have made it a widely used productivity tool.
This article will help you identify the most suitable machine translation software to accelerate the growth of your global organisation.
What is Machine Translation?
Machine translation is the automated translation of text or speech from one source language to another using computational algorithms and AI. Computer software automatically translates texts from one natural language to another using machine translation. The translation process involves inputting text in the source language into machine translation software, which then generates an equivalent translation in the desired destination language.
Machine translation engine uses algorithms and AI to analyse the original language structure, grammatical rules, and vocabulary. This technology can give accurate and contextually appropriate translations in the target language. The process involves complex linguistic analysis, statistical modelling, and a specific machine learning method.
For businesses aiming to expand into global markets, machine translation offers a convenient solution for translating website content, marketing campaigns, and customer communications into target languages. Some have even used a hybrid machine translation strategy that combines machine translation software and human post-editing in their translation workflows to gain a more accurate and tailored to the specific needs of the business.
Some travel companies use machine translation technology to provide services in multiple languages. This facilitates access to information and bookings for tourists from various regions. For example, an agency offering tours on the liberation of Paris would need to translate the content into French, English, and multiple other languages to cater to international tourists. It helps corporations seeking international growth and individuals looking to communicate with others from different linguistic backgrounds.
Common Types of Machine Translation
Image Credit: Phrase
Machine translators employ AI to automatically translate text from one language to another, eliminating the need for a human translator service. Many think that AI like ChatGPT, is leading the way in translation and localization technology as it has made machine translation post-editing more efficient.
Below we have listed 3 main types of machine translation systems: rule-based, statistical, and neural machine translation. We will discuss the strengths and weaknesses of each.
Rule-Based Machine Translation (RBMT)
Rule-based machine translation (RBMT) is an early machine translation engine that uses established linguistic rules to transfer text meaning between languages. It had limitations, requiring extensive human post-editing and manual language insertion, resulting in basic but useful translations lacking fluency and context.
Although rarely used, RBMT still finds applications in precise translation needs, like legal or medical documents. Since its inception, significant advancements in language translation technology have led to newer, more sophisticated approaches, such as statistical and neural machine translation.
These techniques leverage large bilingual dictionaries and corpora and artificial neural networks for more accurate and fluent translations. As a result, rule-based MT is now considered outdated compared to other methods.
Statistical Machine Translation (SMT)
Researchers introduced Statistical Machine Translation (SMT) in the early 1990s. It uses statistical models to create translations based on patterns and frequencies found in large bilingual corpora.
Unlike rule-based machine translation, SMT translation’s quality significantly improves by assessing word and sentence links in multiple languages for more natural-sounding translations. It may struggle with complex sentence patterns, strict linguistic rules, or languages with limited data.
SMT creates a statistical model of word, phrase, and sentence links in a given text, which is then applied to translate the components to the target language. While an improvement over RBMT, statistical machine translation still faces some similar challenges.
Nevertheless, SMT still finds use in older MT systems or specific cases where its qualities are beneficial. Machine translation methods are constantly evolving to achieve smooth and successful cross-lingual communication.
Neural Machine Translation (NMT)
Neural machine translation (NMT) is the most sophisticated type of machine translation. NMT uses deep neural networks to learn and understand the links between words in the source and target language. Unlike previous rule-based techniques, NMT’s neural network handles source text encoding and decoding.
NMT captures contextual information, which results in an accurate and smooth translation process. NMT systems continue machine learning and improve their knowledge with additional training data, much like neural networks in the human brain. This technology is capable of supporting numerous language pairings.
NMT is distinguished from other methods of AI translation by its outstanding accuracy. It also has the benefit of simple language integration and quick translation after the training process. NMT has quickly become the norm in machine translation development because of its capacity to generate excellent translations.
Neural machine translation software has replaced SMT as the preferred approach. NMT processes and translates text using artificial neural networks, resulting in more accurate and contextually relevant translations.
NMT translates any 2 languages with enough training data. NMT has produced some impressive results, even though it’s still under development. In many cases, NMT translations are now indistinguishable from human translators.
Automated vs. Machine Translation: Which way to go?
Automated and machine translation are two terms often used interchangeably, but they represent distinct methodologies in language translation. Computer programs and algorithms help with automated translation, including machine translation, Translation Memory Systems (TMS), and Computer-Assisted Translation (CAT) tools.
The difference lies in the level of human involvement. Automated translation requires human translators’ involvement in working alongside a generalised translation tool to ensure accuracy. Machine translation is fully automated and requires minimal human interaction once set up.
Choosing between these methods depends on factors like the volume of material, required accuracy level, and budget constraints. Machine translation is beneficial for tasks where speed and cost-efficiency are crucial. Businesses that demand higher quality and contextual correctness may prefer automated translation with human control for tasks that require it.
The Best Machine Translation Software
Image Credit: Machine Translation
Machine translation has made remarkable progress in recent years thanks to neural machine translation advancement. NMT has improved machine translation engines to produce translations on par with human-translated content.
Most MT suppliers have embraced NMT in different ways. Some machine language translation offers are free and user-friendly, and others are customised to meet specific business needs. So let’s explore some of the most popular general-purpose MT engines available today.
Google Translate
Google Translate is one of the world’s most widely used machine translation systems, offering translations in over 100 languages.
Google adopted NMT early on. NMT uses artificial neural networks to learn statistical correlations between words and sentences in different languages, resulting in accurate and fluent translations.
Aside from accuracy and fluency, it offers additional features that make it a valuable tool for users. It has real-time text translation, language translation in conversations, and even translates entire websites.
Main Features of Google Translate:
- Support for over 100 languages
- Text and speech translation
- Real-time camera translation
- Offline translation for selected languages
- Integration with Google services
Pricing:
Free to use for individual users. Enterprise plans require a subscription-based pricing model.
Free Trial/Plan:
The basic version is available for free to all users.
Distinguishing Factors:
It’s a user-friendly translation tool because of its vast language coverage, real-time camera translation, and smooth connection with notable platforms.
Amazon Translate
Amazon Translate is an integrated neural-based machine translation service by Amazon Web Services (AWS), introduced in 2017. It has rapidly become a popular choice among translation services in the market.
Amazon Translate uses NMT technology to deliver high-quality translations across various content categories. Its simple API connectivity makes it easy for developers to incorporate translation into their applications. This API makes it a valuable tool for organisations to provide content to their customers in more languages.
Main Features of Amazon Translate:
- Neural Machine Translation for accurate translations
- Support for multiple content types, including text and HTML
- Scalable and efficient translation through AWS infrastructure
Pricing:
Amazon Translate’s pricing is based on the number of characters processed, making it a cost-effective option for businesses of all sizes.
Free Trial/Plan:
Amazon Translate provides a 12-month free trial for new AWS users, allowing them to experience the service without any charges.
Distinguishing Factors:
Amazon Translate’s smooth connection with AWS services and emphasis on meeting the demands of developers make it a good alternative for businesses that already use Amazon’s cloud infrastructure.
DeepL
DeepL Translate is a machine translation engine developed by the German company DeepL SE. It employs a neural machine translation (NMT) model to generate natural-sounding and nuanced translations.
DeepL has gained widespread popularity, with millions of users worldwide relying on it to translate documents, websites, and other information. Professional translators and content creators who appreciate its precision and fluency favour it.
Main Features of DeepL:
- They support a total of 31 languages, with 650 possible translation combinations.
- Context-aware translations for more accurate results
- Usage of existing translations to improve machine-translated output quality
- Support for document translation
Pricing:
DeepL offers both free and premium plans. The premium version has an unlimited number of characters, 5-100 editable documents per user/month, tone of translation, and API integration. DeepL offers both free and premium plans.
Free Trial/Plan:
DeepL offers a free plan that limits the number of available daily translations. The premium plan removes this limitation and unlocks additional features.
Distinguishing Factors:
DeepL is a good choice for organisations and people who want high-quality translations. It emphasises translation quality improvement, has a user-friendly design, and supports 31 languages.
Benefits of Machine Translation
Machine translation is a transformative technology that makes translation workflows more efficient, especially regarding post-editing.
Key benefits of machine translation include:
- Global communication: MT translates marketing materials, product manuals, and customer service content into multiple languages. This eliminates language barriers.
- Time and cost savings: MT reduces the time and resources required for translation tasks, making it cost-effective. Human translators with language skills will be able to focus on more complex translations as they do post-editing.
- Real-time translation: Neural machine translation (NMT) allows real-time translations for instant interactions with customers and partners. MT enables real-time translation in customer service chat conversations or live videos.
- Consistency: MT maintains consistency in translated content for a cohesive brand tone across different languages. Companies translate their product catalogues, marketing brochures, and training materials into various languages preserving a unified vocabulary and style.
- Language learning: MT will assist language learners by providing context and examples of word usage. Translating foreign-language news items or creating flashcards with translated vocabulary terms will aid learners in improving their fluency and comprehension of a new language.
What is Machine Translation: Conclusion
Machine translation engines help global communication by bridging linguistic gaps. Neural machine translations have replaced traditional rule-based approaches to achieve more accurate and fluid translations.
MT services like Google Translate, Amazon Translate, DeepL, and Microsoft Translator offer diverse options to meet the needs of different users. Revolutionising communication across various sectors, translating news stories, product descriptions, and social media content. It finds applications in education, medicine, and tourism.
As MT technology continues to evolve, it will play a vital role in breaking down language barriers further. MT fosters outstanding connectivity among individuals from diverse cultures and nations.
FAQs on Machine Translation
What is an example of machine translation?
An example of machine translation is automated tools that translate text or speech from the language pairs. To give a better example, let’s use one of the commonly known machine translation tools “Google Translate,” to translate the sentence “Hello, how are you?” from English to Spanish, resulting in the translation “Hola, ¿cómo estás?”.
Machine translation is a valuable tool that provides quick and rough translations that give the general meaning of foreign language content. This benefits travellers, businesses involved in international trade, or individuals seeking to understand foreign news articles and websites.
Machine translation engines have also revolutionised real-time communication by breaking language barriers during live chat sessions and video conferences.
What is machine translation good for?
Machine translation is good for various purposes. It effectively translates text from the language pair, opening up opportunities in different fields. Businesses find great value in machine translation.
Language service providers will help reach global audiences by translating their websites, documents, and marketing materials into multiple languages. It broadens their market reach, potentially increasing sales, heightened brand awareness, and enhanced customer satisfaction. For individuals, basic machine translation is a valuable tool to help them understand foreign texts. When travelling, it is handy for translating signs, menus, and other essential information in a foreign country.
Businesses engaged in international trade rely on hybrid machine translation to translate contracts and other crucial documents. Even those interested in reading foreign news articles or websites use MT to grasp the general meaning of the content. Machine translation enables real-time communication by translating conversations during live chat sessions or video conferences. This live translation allows effective communication between individuals who speak different languages.
Is machine translation difficult?
No, machine translation is incredibly user-friendly and accessible to end users, requiring only an internet connection. To use it, you will need to input the sentence you want to translate and select the desired output language.
However, developing sophisticated machine translation poses significant challenges. Ensuring more accurate translations, especially for complex texts or rare languages, requires advanced algorithms, enormous data processing power, and continuous refinement.
Researchers and engineers continuously work to enhance machine translation, aiming for more accurate and contextually appropriate translations. End users find machine translation easy to use. However, developing and training advanced machine translation models are complex for developers and researchers.
Is machine translation possible?
Yes, machine translation is possible. It has become widely used due to significant advancements in artificial intelligence and natural language processing. Although the translation management system may not consistently deliver perfect translations, they serve as valuable tools for global communication.
It’s necessary to acknowledge that machine translation cannot fully replace human translator experts, especially for critical or creative tasks that involve cultural nuances and context. Instead, it complements human translation, making communication more accessible and efficient. Machine translation tools and services range from free online options to premium business solutions.
How does the machine translation work?
Machine translation works by employing algorithms and statistical models to analyse and interpret a text in one language, generating equivalent text in another. It involves analysing extensive bilingual text data to identify patterns and associations between words and phrases in different languages.
Advanced algorithms and artificial intelligence then use these findings to produce translations. With the advent of the neural machine translation system and machine learning algorithms, modern machine translation often combines both approaches, resulting in substantial improvements in translation quality.
Is machine translation accurate?
Yes, machine translation has significantly improved accuracy, thanks to AI and neural network advancement. The translation management system now achieves remarkable precision, especially for widely spoken languages, providing fluent and understandable translations suitable for everyday texts, emails, or website content.
Machine translation still faces challenges in handling context, idiomatic expressions, and domain-specific jargon. Accuracy varies depending on the source text complexity and the availability of relevant training data. Human translation remains the gold standard, ensuring absolute accuracy and cultural appropriateness for critical or professional purposes.
What is a machine language translator called?
Machine language translators are often called “Machine Translation Systems.” Translating text or speech from one language to another without human post-editing. These systems come in different forms, such as online language translation services like Amazon Translate or language-specific translation technology designed for specific industries.
Referred to as “machine translation tools” or “machine translation technology,” these systems play a crucial role in modern communication, enabling interactions between speakers of different languages and bridging language barriers worldwide.
What’s the meaning of machine translation?
Machine translation is the automated translation of text or speech from the language pair using computational algorithms and artificial intelligence. Its primary goal is to break down language barriers and enable understanding and interaction with content in various languages.
This revolutionary technology has transformed global communication, facilitating connections, collaborations, and mutual understanding worldwide. However, caution is necessary when using machine translation for critical or professional tasks that require absolute accuracy and cultural sensitivity.
