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Neural Machine Translation: The Rise of the Thinking Machines

Michael Gallagher
Michael Gallagher
Posted in Zoom Sep 6 · 8 Sep, 2022
Neural Machine Translation: The Rise of the Thinking Machines

What Is Neural Machine Translation and How Has It Changed Global Communication?

Years ago, the idea of a machine that could translate languages in real-time seemed impossible. Today, neural machine translation (NMT) is everywhere—helping businesses, travelers, and students connect worldwide. This article explains how NMT works, how it developed, and why it matters for global business.

Understanding Machine Translation

Machine translation uses artificial intelligence to turn words from one language into another without a human translator. While early systems were clunky, the progress is undeniable.

  • In 1834, Charles Babbage imagined a programmable language translator, but the real breakthrough came in the 1950s with IBM's 701 Translator (IBM, 1954).
  • This early system processed Russian phrases into English in seconds, yet required thousands of hours to program strict language rules.
  • More practical methods arrived only in the past few decades.

Two Types of Early Machine Translation

  • Rule-Based Machine Translation (RMT): This system used grammar and vocabulary rules for each language pair. Developers and linguists spent countless hours shaping every detail of the translation process. It was slow and hard to scale, making it too limited for today's needs.
  • Statistical Machine Translation (SMT): SMT used large collections of existing translations to find and apply patterns. This system offered faster learning because it gathered and analyzed massive amounts of data, improving results over time (Och & Ney, 2003). But SMT still had problems with context, idioms, and sentence structure.

Common Types of SMT

  • Word-based Translation: Focused on one word at a time, leading to errors when translating idioms or complex phrases.
  • Phrase-based Translation: Translated groups of words instead of single words. Google Translate first used this method in 2006, but results were often awkward.
  • Syntax-based Translation: Translated chains of words or phrases rooted in sentence structure, offering more context.
  • Hierarchical Phrase-based Translation: Combined phrase-based and syntax-based methods for more natural translations.

The Rise of Neural Machine Translation (NMT)

NMT is the modern approach to machine translation. Unlike earlier systems that analyze words or rules, NMT uses artificial neural networks—systems modeled after the human brain. These networks can understand entire sentences and learn from context, making translations more accurate and natural.

  • Google revamped its translation system to the Google Neural Machine Translation system in 2016, greatly improving accuracy and speed.
  • Other tech giants like Amazon, Microsoft, and DeepL also rely on NMT in their translation engines.
  • NMT systems use "encoders" and "decoders" to process one language and output another, adapting over time to get better with each use.

NMT's ability to handle large amounts of data and improve itself sets it apart from older translation methods (Wu et al., 2016).

Main Benefits of Neural Machine Translation

  • High Accuracy: NMT produces more accurate translations, especially for full sentences and paragraphs. Its accuracy improves with more training and use in specific languages and fields.
  • Fast Learning: NMT adapts quickly to new terminology, brands, and industries. As the system is exposed to more examples, its translation quality gets better.
  • Scalability: Businesses can increase or decrease translation workloads easily, matching changing needs.
  • Cost Efficiency: Professional translators charge between $30–$70 per hour (The Translation Company, 2023). NMT can greatly lower these costs and still allow for expert proofreading when needed.
  • Easy Integration: NMT systems can be added to customer service platforms or e-commerce websites using APIs and SDKs.
  • Customization Choices: Companies can add their own glossary or adapt NMT for industry jargon.

How Businesses Use Neural Machine Translation

  • Handling High Volumes: NMT processes thousands of documents quickly, ideal for disaster response or global announcements.
  • Translating Customer Reviews: It can translate reviews left by international shoppers, helping brands understand global feedback and share positive testimonials across markets.
  • Supporting Documentation: NMT streamlines the translation of manuals and user guides into several languages, reducing wait times and printing costs.
  • User-Generated Content Analysis: Brands can track and analyze online comments, social media posts, and other feedback from customers worldwide, regardless of language.
  • Improving Customer Support: By translating conversations in real-time, NMT allows for smoother communication between businesses and customers around the world.

What Is the Future of Neural Machine Translation?

Experts predict that NMT will continue to grow as artificial intelligence improves. New techniques and larger data sets will make machine translations even more accurate and nuanced. However, language always evolves, so human translators will still be needed for especially difficult or creative projects (Vaswani et al., 2017).

  • Human translators bring cultural context and handle new slang or idioms.
  • NMT provides speed, volume, and cost savings not possible with only human effort.

The partnership between people and machines will give organizations the best of both worlds—efficient, accurate translation and high-quality human insight.

Need Neural Machine Translation for Your Business?

Neural machine translation offers unmatched speed, accuracy, and scalability for modern businesses. Whether you need to translate technical manuals, customer reviews, reference guides, or real-time chat conversations, NMT can help you reach new markets and connect with global audiences.

GoTranscript is ready to help you take advantage of cutting-edge neural machine translation and related services. Visit our website to find the right solution for your needs.