In today’s fast-paced globalized world, translating vast amounts of content in a short time frame has become crucial for many industries. Machine Translation (MT) plays a pivotal role in meeting these demands. When combined with professional post-editing services—like those offered at tolingo—MT becomes an even more powerful tool for businesses looking to optimize their translation workflows without compromising on quality.
In this article, we’ll explore how you can get the most out of machine translation by diving into the nuances of different MT engines, addressing common concerns about data security, and highlighting the importance of customization for improving translation accuracy and meeting specific organizational needs.
The first step toward effectively utilizing machine translation is understanding that not all MT engines are created equal. Today, dozens of MT engines are available, each developed by various providers with different capabilities. These engines vary in many aspects, such as the language combinations they support, how they handle tags, and ultimately the quality of the translations they deliver.
For example, some MT engines excel in processing European languages, while others may be better suited for Asian languages. The engine’s ability to manage technical jargon and idiomatic expressions can also vary significantly depending on its training data and algorithms.
One of the most overlooked aspects of using MT tools is the issue of data security. When you upload texts to publicly available MT engines, you are entrusting your data to third-party providers. Some free or publicly accessible MT tools may store the uploaded data, often using it to improve their algorithms by incorporating your content into their training data. While this can be beneficial for enhancing the engine’s performance, it also poses a potential security risk, especially if the content is sensitive or confidential.
For example, companies in industries like finance, law, or healthcare typically deal with documents that contain personal data or proprietary information. Uploading such documents to an MT engine that stores this data could expose the company to privacy breaches, regulatory non-compliance, and potential legal liabilities.
At tolingo, we take information security very seriously. Specifically, we collaborate with providers that are ISO 27001 certified, demonstrating their commitment to handling data with the utmost care and security. This certification confirms that the providers have implemented strong information security management systems, helping to reduce the risk of data breaches or unauthorized access.
While general-purpose MT engines are impressive, their performance can improve through customization. Many MT engines today offer customization options, allowing users to tailor the engine to a specific corporate language. For example, engines can be trained with specialized terminology, which results in more accurate and context-appropriate translations.
With the right training data and expertise, customization can significantly improve the MT-output. At tolingo, we can customize the MT-Output in order to ensure consistent MT-outputs and reduce the amount of time needed for post-editing.
While machine translation has come a long way, it’s important to acknowledge that it’s not always perfect—especially when it comes to complex or nuanced content. This is where professional post-editing comes into play. At tolingo, we offer two levels of post-editing services, depending on the level of precision you require. Light post-editing aims at bringing the translation to an acceptable level of accuracy by correcting obvious errors and conveying the content of the original text. Full post-editing, on the other hand, involves a thorough stylistic review, making sure that the text is idiomatic and adapted for the target audience.
Another factor that’s often overlooked when considering machine translation is file format compatibility. Many online MT tools are limited in the types of file formats you can upload. For instance, while translating plain text or Microsoft Word documents is relatively straightforward, more complex file formats like HTML, XML, or subtitle files (e.g., .srt) may not always be supported by online MT engines. Also, data integrity is essential: you might deal with file formats containing sections that should be left unchanged to preserve functionality or ensure proper display, such as code snippets or formatting tags. If these elements are altered during machine translation, it can result in broken code or disrupted formatting in the final output.
At tolingo, we address this challenge by using a combination of Computer-Assisted Translation (CAT) tools and MT engines. This integrated workflow ensures that almost any file format can be processed seamlessly, allowing us to maintain the integrity of the original document.
The future of machine translation is advancing rapidly, fueled by breakthroughs in artificial intelligence, particularly large language models (LLMs) like GPT, Claude, and Llama. At tolingo, we are closely monitoring these developments and actively testing various use cases to explore their potential. The possibilities are exciting, from automated quality checks to MT-output optimization.
Stay tuned for further updates!