5 Easy Ways to Improve the Quality of Your A.I. Translations

An increasing number of businesses, primarily in the financial and legal sector, are now leveraging Artificial Intelligence (A.I.) translation solutions to improve quality and efficiency. 

A.I. has allowed us to translate documents quickly and accurately. However, this does not mean that all A.I. translations are perfect. 

Because A.I. uses machine learning, the system is always adapting, becoming more accurate with every translation it completes. There are a few simple ways by which you can improve the quality of your A.I. translation output.

Neural Machine Translation + Machine Learning = New Role of Translators

Modern translation technology uses automated Neural Machine Translation (NMT) systems to predict the likelihood of specific word sequences. For instance, certain phrases do not always translate well into other languages,  such as “all and sundry.” 

The machine mimics human logic using A.I., enabling it to spot errors, trends and patterns. This means it can contextually translate phrases to ensure that the meaning is not lost in translation. 

Users can import past translations to teach NMT engines to recognize the source and target connections. The more you provide to the NMT platform, the more accurate it becomes.

As a result, a trained NMT engine is better able to choose the proper term to use in each circumstance without being specifically programmed to do so. It can identify and self-correct its mistakes, using reason to draw conclusions about context and meaning. 

But what of the actual translator? How does their role evolve?

With the advancements in A.I., traditional translators are able to get more done in a shorter time period. The A.I. model can be trained to perform repetitive translation tasks, freeing up translators to perform more accurate post-edits and work on high-priority projects.

5 Ways to Improve The Quality of Your A.I. Translation Output
1. Determine What “Quality” Means for Your Organization

If you are leveraging A.I. translations, it is important to understand that the quality of translation might not be consistent, especially if input documents are not properly formatted. 

Here are some key considerations when determining what "quality" means for your organization: 

Accuracy: Even minor errors in translation can result in significant consequences, such as legal disputes or financial losses. You should check that your A.I. translation output accurately captures the meaning of the source text, including legal and financial terms and concepts. 

Consistency: Consistency ensures that the translation is uniform, clear, and easy to understand. Check that your A.I. translation output is consistent with your organization's terminology, style, and tone. 

Confidentiality: Legal and financial documents often contain sensitive information that must be kept confidential. Confirm that your A.I. translation output is secure and meets your organization's confidentiality requirements. 

Turnaround time: Ensure that your A.I. translation system can provide translations quickly and efficiently without sacrificing accuracy. 

Regulatory compliance: Legal and financial documents must comply with various regulations and requirements, especially related to data security and protection.

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2. Establish a Feedback Process

When implementing A.I. translation software, it is important to view it as a long-term investment rather than a one-time setup. The software will continue to improve over time, but it requires training to align with the specific translation needs of your business. 

Establish a feedback loop between your IT department and translators to ensure optimal performance. This allows organizations to identify areas that require improvement and facilitates the incorporation of necessary updates.

If your A.I. translation software partner offers you a dedicated account manager, share your feedback with them. They may be able to offer suggestions on creating term bases or managing translation memories, and your feedback might even inform opportunities to improve the platform as a whole.

3. Make Sure That Your Source Text Is Clean

Before submitting source text for translation by your A.I. platform, take the time to review and edit it for accuracy. This includes correcting any typos or grammatical errors. 

To ensure a smooth translation process, it is important to use a writing style that is clear and concise.

Additionally, use language that is easy to understand and avoid complex grammar, jargon, idioms, colloquialisms, and abbreviations. 

Remember also to consider the unique characteristics of the language pair in question. For example, the grammar and syntax required for an English-to-Chinese translation may differ greatly from that of an English-to-French translation.

4. Regularly Update Base Data

The accuracy and effectiveness of A.I. translation software depends heavily on the quality of its training dataset - a language corpus consisting of language pairs that includes relevant terms that are reused again and again. 

Machine translation uses artificial intelligence to automatically translate to and from different languages, without requiring any human input. It uses large databases, pre-populated translation memories, term bases, and a large corpus of text to improve the quality of your translations. 

The software is able to recognize syntax specific to your industry and pick up new terminology from previous dictionaries. It can also be customized within a few days and new words and terms can be added continuously. 

However, it is crucial to remember that maintaining a trustworthy A.I. translation platform that delivers top-tier results for your organization takes ongoing effort. Encourage all team members to contribute to the training dataset by providing high-quality, relevant information based on your industry. 

Consistency in terminology and frequent evaluations of data relevance are key to achieving deep customization for your business. Run tests on a regular basis to confirm that the A.I. translations meet your standards.

5. Regularly Train the Computer With Post-Editing Corrections

Post-editing corrections play an important role, as it ensures that the A.I. translations are more specific to your business industry. 

This is important as the feedback you input in the A.I. translations engine helps improve the quality in the long run. This is critically important, as the system uses machine learning and continues to improve.

We Are Here to Help

The translation industry is changing significantly because of A.I. translations. Consequently, translators’ jobs will change going forward. 

With A.I. translations, you can concentrate on exciting activities like pre-processing, post-editing, polishing automated translations, quality checking, and computer training. 

As a creative, specialized subject matter expert, you will have to use your unique talents to perform these jobs.

Similar logic, of course, applies to every other user who is not a translator by trade. Using A.I. translations and following best practices can play an important role in making sure that the translation engine is specific to your needs. 

The Alexa Translations A.I. is specifically trained for the Canadian legal, financial, and securities sectors. It provides complex, industry-specific translations with unrivaled quality and speed.

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