Machine Translation | Definition, Uses & Benefits
Machine translation is the use of software to translate from one language to another. This type of software is usually powered by AI.
Spanish output: ¡Qué perro tan hermoso!
Source: QuillBot’s Translate
In the example above, I used a tool that performs machine translation, which translated this phrase automatically. I then reviewed it, and as someone who speaks both languages, I found the translation to be accurate (“perro” is dog in Spanish, and “hermoso” is one way to say beautiful).
What is machine translation?
Machine translation is the use of computers to convert text or speech from one language to another. Unlike traditional translation, which requires a human translator, machine translation uses algorithms and vast datasets to produce translations instantly.
As it can process large amounts of text quickly, machine translation is valuable for high-volume translations. This, combined with the continuing advances in AI, has made machine translation a popular solution for breaking down language barriers.
There are different types of machine translation tools. Some, like QuillBot’s Translator, are strict translation tools. Others, like ChatGPT, are chatbots that can translate text and also take on other generative AI tasks, like content creation.
How machine translation works
Machine translation takes one language (the “source” language) as input and produces a second language (the “target” language) as output. The underlying process depends on which computational methods the translation tool uses.
Rule-based
Rule-based machine translation uses a set of grammar rules and dictionaries to translate word by word. It follows the syntactic structure of both languages. While effective for simple text, it can struggle with complex sentence structures, idioms, and tone.
This type of machine translation is sometimes used in technical and legal translations, where strict terminology and consistency rules apply.
Statistical
Statistical machine translation employs statistical models trained on large datasets of parallel texts (the same text in two languages). When asked to translate a word, it determines the most likely translation based on statistical probabilities. It tends to produce more fluent translations compared to rule-based translation, but it may still struggle with certain nuances of language.
Statistical machine translation was the dominant method in the past (e.g., Google Translate used to rely on it), but it has mostly been superseded by neural machine translation.
Neural
Neural machine translation is powered by artificial neural networks that process language in a way that captures contextual relationships between words. They use natural language processing (NLP) to approach language similarly to how a human would. Neural machine translation is capable of processing entire sentences or paragraphs at once, leading to more fluent and natural-sounding translations.
Neural machine translation can also improve over time when trained on additional data or refined through user feedback. It’s currently the most advanced form of machine translation.
Many translation tools (e.g., ChatGPT, DeepL) now rely on neural machine translation.
Output: In Greek, you can say:
“Γειά σου! Πώς είσαι; Πώς ήταν η μέρα σου;”
(Transliteration: Geia sou! Pos eisai? Pos itan i mera sou?)
This is informal and friendly, perfect for reaching out to a friend.
Source: ChatGPT
Since ChatGPT uses neural machine translation, it was able to translate beyond just words, catching nuances like differences in punctuation.
How machine translation is used
Machine translation has many applications across diverse fields. Below are some examples.
| Field | Use |
|---|---|
| Travel | Helps travelers navigate foreign countries by translating signs, menus, directions, and essential phrases |
| Content creation | Assists content creators in localization of their work, making blogs, articles, and social media posts accessible to a global audience |
| Business and marketing | Translates product descriptions, customer support materials, website copies, and marketing campaigns for international audiences |
| Public administration | Allows government organizations like the European Commission to more rapidly translate information into various languages |
| Social media | Enables users to access content and communicate in other languages in real-time |
| Encyclopedias and dictionaries | Provides platforms like Wikipedia the ability to translate content in multiple languages and reach a global audience |
| Language preservation | Helps document and preserve endangered languages |
Benefits and limitations of machine translation
Machine translation offers many benefits, like:
- Speed – Machine translation is fast, providing translations in seconds.
- Scalability – Since computers can translate large amounts of text fast across various languages, they can translate content at scale without increased human effort.
- Cost savings – It eliminates the need for expensive professional translation services, making it an affordable solution.
- Improved accessibility – Machine translation opens doors for people with limited access to professional translators, allowing for broader, more diverse communication.
- Capacity to improve – AI improves as it processes more data. This means machine translation tools become more accurate as they “learn” from previous translations.
- Cultural and historical value – Machine translation may help preserve endangered languages from extinction.
While machine translation is always evolving, it still has some limitations:
- Potential bias – Machine translation tools are only as good as the data they’re trained on. If training data is biased, those biases may show up in the tool’s translations. Likewise, if training data is limited in quantity and quality, that might be reflected in the quality of machine translation. For example, translations of minority languages may not be as robust as translations of global languages.
- Difficulty with nuance – While it has improved a lot, machine translation still sometimes struggles with context, tone, and idiomatic language. Sarcasm, humor, and figurative language might be particularly challenging.
- Lack of cultural sensitivity – Machine translation tools may not be able to pick up on culturally sensitive elements of language, leading to translations that could be perceived as inappropriate or offensive in certain contexts.
Frequently asked questions about machine translation
- What is machine translation software?
-
Machine translation software is a type of computer program that uses algorithms and AI to automatically translate text or speech from one language to another without human intervention.
These tools range from simple word-for-word translation programs to advanced AI-powered systems that are capable of understanding more complex nuances in language, like tone or idioms.
An example of machine translation software is QuillBot’s free Translator.
- What’s machine translation vs. CAT?
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The main difference between machine translation vs. CAT (or “computer-assisted translation”) is that CAT software is designed to assist human translators, while machine translation is designed to be automatic.
QuillBot’s free Translator is one example of a machine translation tool.
- What is neural machine translation?
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Neural Machine Translation (NMT) is an advanced form of machine translation that uses deep learning and artificial neural networks to translate text from one language to another.
Unlike older methods of machine translation, NMT processes entire sentences at once, considering context and linguistic structures (e.g., compound subject or double negative) for more fluent and accurate translations.
One example of a machine translation tool is QuillBot’s Translator.
