A Simple Guide to Enterprise Machine Translation

Not every business can afford a human translator, and even those who can, may find the manual translation process time-consuming.

But there’s a middle ground. Enterprise machine translation (EMT).

EMT is designed for businesses and can tackle large batches of translation efficiently, especially when paired with human editors.

This guide will introduce you to the basics of EMT, the different kinds available, things to consider when choosing one, and some of the best options out there to help your business communicate better worldwide.

Pro tip: EMT saves time, but human editors enhance accuracy. Centus combines both in one easy-to-manage platform. Learn how.

What is enterprise machine translation software?

Enterprise Machine Translation (EMT) software is a type of translation software used by enterprise businesses in extensive localization projects. Unlike basic translation tools, EMT software has advanced features that let businesses manage and organize their translation projects more efficiently.

Companies use enterprise-level MT solutions in the following cases:

• Communications: Respond to international clients and staff in their native language.
• Document translations: Translate documents, manuals, or reports efficiently.
• Website localization: Make your website accessible to a global audience.
• Customer support: Provide multilingual support without delay.
• Marketing material: Translate marketing content to reach a wider audience.
• Product descriptions: Translate product information for diverse markets.

Types of enterprise machine translation

Machine translation software comes in various flavors, each with its unique approach to translating text. The right type for your business depends on your specific needs, whether it's accuracy, speed, or a balance of both. We’ll explore the primary types of EMT, how they function, and the situations where you’ll need each one.

1. Rule-based machine translation (RBMT)

RBMT operates on linguistic rules and dictionaries for both the source and target languages. It translates text based on grammatical rules and the meanings of words. How it works: RBMT follows a systematic process to translate phrases or sentences. Initially, the system identifies the grammatical rules of the source language, recognizing the roles of verbs, nouns, adjectives, and other parts of speech. Next, it consults dictionaries to find the equivalent words or phrases in the target language. Lastly, it applies the grammatical rules of the target language to arrange the translated words in a way that makes sense.

For example, with a sentence like The cat sat on the mat, the system would first recognize the verb sat, the nouns cat and mat, and the preposition on. It would then find the Spanish equivalents for these words, and finally, rearrange them according to Spanish grammar to produce El gato se sentó en la alfombra.

Best for: RBMT is the oldest type of EMT and has been around since the 1970s. However, it's less popular now due to its limitations in handling language nuances. However, RBMT is best machine translation software for businesses with very formal or structured text, like legal or technical documents.

2. Statistical machine translation (SMT)

SMT learns from existing translations to predict how new texts should be translated.

How it works: SMT analyzes large amounts of translated text to find patterns and make educated guesses on translating new text.

Consider the sentence The quick brown fox jumps over the lazy dog. Translated using Apertium (RBMT), it becomes: El zorro marrón rápido salta el perro perezoso. With NiuTrans (SMT), it's: El ágil zorro marrón se saltó al perro perezoso.

The SMT translation opts for ágil (nimble) over rápido (quick) and uses a more native-like verb phrase se saltó al (jumped over), showcasing SMT's ability to provide a more natural and fluent translation. Best for: SMT can handle more language pairs and informal text compared to RBMT. It also requires less human intervention compared to RBMT, but a substantial amount of bilingual text data to learn from. It’s typically best for businesses with access to large bilingual text datasets for machine translations.

3. Neural machine translation (NMT)

NMT is a newer, more advanced form of machine translation that uses neural networks to improve translation quality and leverages techniques from natural language processing.

How it works: NMT analyzes text as a whole, understanding context to provide more accurate translations. Unlike SMT, which translates phrases or sentences in isolation, NMT takes into account the broader context.

In 2016, Google Translate switched to NMT, significantly improving its translation quality.

Consider the translation of the quick fox phrase on Google Translate: El rápido zorro marrón salta sobre el perro perezoso.

It reflects better contextual understanding compared to RBMT and SMT. It shares RBMT's choice of rápido (quick) over SMT's ágil (agile), and accurately translates the verb phrase as salta sobre (jumps over) unlike RBMT's salta (jumps) and SMT's se saltó al (jumped over). NMT correctly uses el before perro perezoso (the lazy dog), unlike RBMT and SMT, showcasing its superior contextual and grammatical comprehension, leading to a more natural translation.

Best for: NMT translations are often closely similar to human translation. They are great for businesses looking for high-quality translations, especially in customer-facing materials.

4. Hybrid machine translation

Hybrid MT combines elements of RBMT, SMT, and NMT and leverages the strengths of all three machine translation systems.

How it works: Hybrid MT might use RBMT for grammatical structure, SMT for phrase translations, and NMT for context understanding. Some computer-assisted translation platforms use Hybrid MT to ensure both accuracy and efficiency in translations.

Best for: Hybrid solutions can offer a good balance between translation speed and quality. It is best for businesses with varied translation needs, looking for a balanced solution.

Each type of EMT has its strengths and ideal use cases. The choice between them depends on your business needs, your own language, and the resources you have at hand. Understanding these types will help you make an informed decision when choosing a machine translation technology.

Tips for choosing an enterprise machine translation solution

Not all EMT engines are created equal.

A report by Intento shows that out of 37 machine translation engines evaluated, 23 are top performers in certain language pairs and domains.

So, how do you choose the right EMT engine?

The short answer is to use the engine suitable to your business niche and target language pairs. The longer answer is below.

1. Accuracy

Accuracy in machine translation refers to the correctness and fluency of the translated text. It is the extent to which the translated content faithfully represents the original text's meaning.

Questions to ask:

• How does the MT engine ensure translation accuracy?
• Are there any accuracy benchmarks or metrics provided?
• Is there a way to improve accuracy through training or feedback?
• How accurate are the translations provided by the engine?

High accuracy is important as it ensures that the intended message is conveyed without loss of meaning, which is crucial, especially in legal, medical, or technical translations where a misinterpretation could have significant consequences.

2. Integration

Integration refers to the capability of the machine translation solution to seamlessly work with existing systems, software, or workflows that a business already has in place.

Questions to ask:

• How easily can the MT solution be integrated with existing systems?
• Are there APIs or plugins available for integration?
• Is there technical support available for the integration process?
• How seamless is the integration with your translation management system (TMS) or other tools?

Easy integration minimizes the time, effort, and cost involved in adopting a new machine translation solution.

3. Support and updates

Make sure to check for the availability of technical support and regular updates to improve the machine translation system.

Questions to ask:

• What levels of support are available?
• How often are updates released?
• Are there additional costs for support and updates?

Continuous support and updates are crucial to address any issues, ensure the system stays current with the latest translation models, and adheres to evolving industry standards.

4. Domain specialization

Domain specialization refers to how well a machine translation system can handle specific areas like medical, legal, or technical topics. When a translation system knows the lingo of a particular field, it's more likely to get the translations right.

Questions to ask:

• Does the MT solution offer domain specialization?
• How does it ensure accuracy within specialized domains?
• Can the system be trained or customized for a specific domain?

Domain specialization is crucial in fields like law or medicine, where every term can carry a lot of weight.

5. Language pairs

Language pairs refer to the languages that the machine translation system can translate between, e.g., English to Spanish, French to German, etc.

Questions to ask:

• What language pairs are supported?
• Is the accuracy consistent across different language pairs?
• Can additional language pairs be added or customized?

The more language pairs a system supports, the more versatile it is for different translation needs.

6. Cost

This refers to the pricing structure of the machine translation engine, including the initial cost, subscription fees, and any additional charges. A business might opt for a subscription model that allows for a certain number of translated words per month, with additional costs for extra translations or specialized support.

Questions to ask:

• What is the pricing model of the MT engine?
• Are there any additional costs for support, updates, or extra features?
• Are there different pricing tiers, and what do they include?

Understanding the cost helps you check if it fits within your budget while meeting your translation needs. It also helps in assessing the return on investment the MT engine provides.

7. Security and compliance

This involves the measures taken by the machine translation engine to safeguard your data and ensure compliance with industry standards and regulations. For instance, a healthcare organization would require a machine translation engine that complies with Health Insurance Portability and Accountability Act (HIPAA) regulations to safeguard patient information.

Questions to ask:

• How is data security and privacy ensured?
• Does the MT engine comply with industry standards and regulations?
• What are the data retention policies?

Security and compliance are crucial to keep your data safe and to make sure you're following the law. This way, you avoid legal troubles and keep your organization's good name intact.

Other significant considerations include:

• Customization: How well can the MT engine be tailored to your specific translation needs?
• Scalability: Can the EMT solution handle your growing translation demands?
• Ease-of-use and training: Is the solution user-friendly? Are there training resources to help your team get acquainted with the system?

After considering the factors above, make sure to talk to an enterprise machine translation provider to better understand how their solution aligns with your business needs.

When you take the time to make a well-informed choice, you’ll end up with better translations, smoother operations, and an easier time connecting and communicating across the globe.

5 Recommended enterprise machine translation solutions

Choosing the right machine translation solution can be a game changer for both your domestic and international business. Here are some of the top enterprise machine translation solutions that could be the perfect fit for your language translation needs.

1. DeepL

DeepL Pro for Business is designed to help businesses break language barriers and communicate in other languages. Its translations are known for their human-like quality, which can significantly cut down localization costs.

Pros:

• They claim high translation accuracy compared to competitors.
• Can be integrated into different operational setups to speed up translation processes.
• Offers enterprise-level data security with end-to-end encryption.
• Supports unlimited translation volumes.
• Retains original document formatting during translation.

Cons:

• Limited language pairs compared to some competitors.
• Cost may be high for small businesses or high-volume translation needs.

DeepL is great for businesses that need translations to feel natural and human-like, especially if they talk to international clients a lot. It's also good for businesses that have a lot of text to translate but want to keep the original look of their documents.

2. Google Translate

Google Translate is an advanced machine translation service by Google. It provides businesses with the capability to translate large volumes of text across multiple languages swiftly.

Designed for scalability and accuracy, it assists companies in global communication and content localization. While it builds on the foundation of the consumer-facing Google Translate, the enterprise version offers more robust features tailored to business needs.

Google Translate is available across different platforms, like web, Android, and iOS​.

Pros:

• Free to use and user-friendly.
• Quick translations for small texts and specific words.
• A vast number of supported languages.
• Improved accuracy over time with a variety of functions to enhance translation quality.
• Capable of translating a wide variety of text formats.
• Available on multiple platforms.

Cons:

• May present errors in translations, especially for long texts.
• Some features may only be available for certain languages.
• Due to the wide language support, error correction might be slower.

Google Translate could be a go-to solution for individuals or businesses that need quick translations for short texts across a wide range of languages. It's especially useful for those who engage in international communication on a basic level. However, for more accurate or domain-specific translations, other solutions might be more suitable.

In addition to the basic Google Translate, Google has also ventured into a more business-oriented solution known as the Google Enterprise Translation Hub. This hub will and has helped bring translation services closer to business users.

3. Microsoft Translator

Microsoft Translator is a tool from Microsoft that turns text from one language into another. It's part of a bigger set of online services by Microsoft known as Azure. This tool is good for businesses or app creators who need to handle translations either on the spot or all at once for different projects.

Pros:

• Supports a wide range of languages.
• Real-time and batch translation capabilities.
• API available for easy integration into various platforms.
• Custom translation feature allows for domain-specific translation customization.
• Continuous updates and improvements based on user feedback and data analysis.

Cons:

• Some users may find the setup and integration process a bit technical.
• The translation quality may vary for less common language pairs or complex sentences.

Microsoft Translator is a good choice for businesses or people making apps who need a tool that can handle lots of translations. It's great if you want to add translation features to your app or website, or if you work in a special area like law, medicine, or tech where you need translations to be spot on with certain terms.

4. IBM Language Translator

IBM Language Translator, part of IBM's Cloud Services, is an enterprise-focused machine translation tool designed to assist businesses in breaking down language barriers. Using advanced AI and neural network algorithms, it ensures efficient and quality translations tailored to the needs of global companies.

Pros:

• Handles large volumes of text across various languages seamlessly.
• Easily integrates with business applications and workflows.
• Known for stringent data protection standards.
• Allows businesses to train custom models for industry-specific terminology.

Cons:

• As a premium service, it may be more expensive than some alternatives.
• Might require technical know-how for full utilization and customization.

IBM Translator is ideal for medium to large enterprises needing accurate and industry-specific translations, especially those who prioritize data security and seamless integration with existing systems.

5. Amazon Translate

Amazon Translate is a neural machine translation service is a part of Amazon Web Services (AWS). It uses deep learning models to provide fast, scalable, and dynamic translation between numerous languages. Amazon Translate is designed for a broad array of applications like content localization, user-generated content translation, and real-time translated communication.

Pros:

• Seamlessly handles varying volumes, from small texts to large-scale document translations.
• Being part of AWS, it easily integrates with other Amazon services and tools.
• Users can define and use custom terminologies to ensure consistent translation of brand names, technical terms, etc.
• As a neural-based translation service, it benefits from continuous model training and refinement.
• Supports a wide range of languages and is continuously expanding.

Cons:

• As with most AWS services, users pay for what they use, which can become costly for high volumes.
• Might require some technical knowledge, especially for custom integrations and advanced features.
• While it offers custom terminologies, it doesn't provide full model customization like some other services.

Amazon Translate is ideal for businesses of all sizes that need dynamic and scalable translation services, especially those already invested in the AWS ecosystem. It's particularly useful for content localization, real-time communication, and any application requiring integration with other AWS services.

Pro tip: After choosing an EMT engine, use a localization management platform to automate translation workflows, ensure translation quality, and simplify translation implementation. Learn more.