Fuzzy matching

Fuzzy matching is a feature in translation tools that identifies segments in a translation memory that are similar, but not an exact match, to the current text. It helps translators reuse existing translations and saves time on repetitive tasks. This feature is particularly useful when there are slight differences in wording, punctuation, or formatting between segments.

For example, if a Localazy user translates “The user guide is available” and later encounters “The user manual is available,” fuzzy matching can suggest the previous translation with a similarity percentage. The match percentage indicates how closely the suggestion aligns with the new text, making it easier for translators to make quick adjustments while maintaining consistency.

👬 Fuzzy matching at a glance: #️⃣

• Suggests translations from memory that are close but not exact matches.
• Displays a percentage to show how similar the match is to the current segment.
• Reduces repetitive work by reusing existing translations with minor edits.
• Ensures consistency in terminology and style across translations.
• Widely used in Computer-Assisted Translation (CAT) tools.

In the end, fuzzy matching helps translators work more efficiently by providing suggestions from previous translations that are close but not identical. This saves time as well as costs.