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Use AI matching to instantly find and hire professional MT post-editors for any language pair on the Smartcat Marketplace.

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Manisha Singhal

Hindi to English MT post-editor
from Kanpur

rating

10.0

(14)

I am a freelancer professional certified translator

Raphaelle Hoffmann

French to German MT post-editor
from Berlin

rating

10.0

(1)

I am native German & Luxembourgish speaker - My source languages are French / English / German

Andrea Marolt

English to German MT post-editor
from Lisbon

rating

10.0

(247)

It is my passion to translate other languages and to make them understandable to the reader in a meaningful way.

Sam Huang

English to Chinese (traditional) MT post-editor
from Taipei

rating

10.0

(5)

Being a full-time EN-TC and EN-JP freelance translator with around 15-year working experience in localization industry, every chance of cooperation with any potential vendors is my treasure and also pleasure. I am specialized in translation, review, and QA jobs of any projects focusing on various fields such as IT, Computer, Hardware/Software, Marketing, Travel, Consumer Electronics, Network, Measurement, Advertising, Business and Communication, etc. Also, the mainly involved types of projects range from User Interface, User Manual/Guide, Technical Guide to Website contents, etc. Looking forward to hearing from you all if there will be any valuable cooperation chance of localization jobs, and also highly expecting to work with you all soon in the near future.

Peter Pakan

English to Slovak MT post-editor
from Zilina

rating

9.8

(19)

I am skilled at translating English text to Slovak language. I have been working for Gengo-Lionbridge online web platform since 2017 as member of freelance translators´ team. By now I have translated more than 230 000 English words at this platform. Final receivers of my translations were entities such as Amazon, New York Times, Sony, Rakuten, Bloomberg or US Department of State. The fact that I have been part of the translators´team without any interruption since the beginning in 2017 demonstrates high quality and accuracy of my translations. I am passionate about being focused on detail, always considering context of the translated text and finding the most naturally sounding version of the translation. I am always trying to do my best and find room for improvement on order to bring the best possible value to customer and maximise his satisfaction.

Tyler Payne

English to English MT post-editor
from XIamen

rating

9.8

(1)

A patient, helpful copyeditor.

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Smartcat Marketplace FAQ

How does Smartcat AI translation work?
Smartcat AI translation works by utilizing a combination of machine learning algorithms and neural networks to automatically translate text from one language to another. Here is a simplified explanation of the process: 1. Training the AI: The AI model is trained using a large amount of bilingual data, including parallel texts and previously translated documents. This helps the AI learn the patterns and structures of different languages. 2. Preprocessing: Before translation, the text is preprocessed to remove any unnecessary elements, such as formatting tags or special characters. This ensures that the AI focuses on the actual content. 3. Sentence segmentation: The text is divided into individual sentences, as the AI translates one sentence at a time. This helps maintain context and improves translation accuracy. 4. Word alignment: The AI aligns the words in the source sentence with their corresponding words in the target language. This alignment helps the AI understand the relationships between words and phrases. 5. Neural network translation: The AI uses a neural network model, such as an encoder-decoder architecture, to generate the translation. The encoder processes the source sentence and converts it into a numerical representation, while the decoder generates the translated sentence based on this representation. 6. Post-processing: After translation, the text goes through post-processing steps to improve the quality. This may involve fixing grammar, adjusting word order, or applying language-specific rules. 7. Quality assessment: The translated text is evaluated using various metrics and quality checks to ensure accuracy and fluency. This helps identify any errors or areas that need improvement. 8. Continuous learning: The AI model is constantly updated and refined based on user feedback and new training data. This iterative process helps improve the translation quality over time. It's important to note that while AI translation has made significant advancements, it may still have limitations and may not always produce perfect translations. Human review and editing are often necessary to ensure the highest quality translations.