Unparalleled Accuracy with Subtitle-Specific Machine Translation
MediaCAT stands out as the best-performing machine translation (MT) engine, specifically designed for subtitle translation in the Media and Entertainment domain. Consistently voted the top choice by global industry experts, MediaCAT’s performance is backed by rigorous blind testing conducted by our partners.
In a recent independent blind test involving eight leading neural machine translation (NMT) engines, MediaCAT emerged as the clear winner, delivering exceptional accuracy. Why does MediaCAT outperform competitors in this highly competitive market? The answer lies in our use of “golden data.”
What is Golden Data?
Golden data refers to the high-quality, domain-specific data we use to train our MT engines. Unlike other solutions that rely on scraped, untargeted datasets, MediaCAT exclusively uses meticulously QCed subtitle files approved by industry experts. These files originate solely from the Media and Entertainment industry, ensuring relevance and precision.
Generic MT engines, trained on diverse and untargeted datasets, often fail to produce subtitle-ready translations. Even when they deliver acceptable translations, significant human editing is required to refine them. In contrast, MediaCAT consistently delivers outputs that require far less post-editing. This is because our engine is trained using a perfect subtitle dataset - our golden data - designed to meet the specific demands of subtitle localization.
Advanced Engine Processing for Superior Results
Having high-quality training data is just one part of the equation. To achieve exceptional performance, the engine must also process the data intelligently. MediaCAT excels in both areas. So what sets MediaCAT apart? It is its ability to understand context - a crucial factor in media localization.
For example, consider the English-to-French translation of the phrase:
“I like this flower. Put it in the bag.”
MediaCAT translates this correctly as:
“J'aime cette fleur. Mettez-la dans le sac.”
The key here is the correct use of the feminine pronoun “la” to refer to the feminine noun “fleur” (flower). Many competitors’ engines mistakenly use the masculine pronoun “le”, resulting in an inaccurate translation. MediaCAT’s contextual understanding ensures accurate pronoun usage by recognizing the relationship between sentences. This is just one of countless examples where MediaCAT demonstrates superior contextual awareness, significantly reducing the need for manual corrections.
Why MediaCAT is the Industry Leader
MediaCAT’s unmatched performance stems from a combination of curated golden data and a state-of-the-art MT engine designed to leverage this data effectively. By focusing exclusively on subtitles, MediaCAT has established itself as the go-to solution for media localization professionals who demand accuracy, efficiency, and minimal post-editing.
Ready to experience the difference? Discover how MediaCAT can transform your media localization workflow today.
Learn more about how MediaCAT can redefine your localization workflow here
