Lingvanex Tranalator

Translator for

Translation Quality Report March 2024

The goal of this report is to showcase the translation quality of Lingvanex language models according to two most popular machine translation evaluation metrics. Flores is open-source and publicly available data test set that was released by Facebook Research and has the biggest language pair coverage.

Quality metrics description

BLEU

BLEU is an automatic metric based on n-grams. It measures the precision of n-grams of the machine translation output compared to the reference, weighted by a brevity penalty to punish overly short translations. We use a particular implementation of BLEU, called sacreBLEU. It outputs corpus scores, not segment scores.

References

  • Papineni, Kishore, S. Roukos, T. Ward and Wei-Jing Zhu. “Bleu: a Method for Automatic Evaluation of Machine Translation.” ACL (2002).
  • Post, Matt. “A Call for Clarity in Reporting BLEU Scores.” WMT (2018).

COMET

COMET (Crosslingual Optimized Metric for Evaluation of Translation) is a metric for automatic evaluation of machine translation that calculates the similarity between a machine translation output and a reference translation using token or sentence embeddings. Unlike other metrics, COMET is trained on predicting different types of human judgments in the form of post-editing effort, direct assessment, or translation error analysis.

References

  • COMET - https://machinetranslate.org/comet
  • COMET: High-quality Machine Translation Evaluation - https://unbabel.github.io/COMET/html/index.html#comet-high-quality-machine-translation-evaluation

On-premise Private Software Updates

New version - 1.22.0.

Changes in functionality:

  • Add support for audio in video files for Speech Recognizer.

New version - 1.21.1.

Changes in functionality:

  • Fixed speech recognition in *.wma and *.flv files.

Improved Language Models

BLEU Metrics

Improved Language Models. March 2024

COMET Metrics

Improved Language Models. March 2024

Language pairs

Note: The lower size of models on the hard drive means the lower consumption of GPU memory which leads to decreased deployment costs. Lower model size has better performance in translation time. The approximate usage of GPU memory is calculated as hard drive model size x 1.2


More fascinating reads await

Join the race: Machine translation in the automotive industry

Join the race: Machine translation in the automotive industry

June 04, 2024

How to translate a website?

How to translate a website?

April 30, 2024

Simplified Technical English (STE)

Simplified Technical English (STE)

April 29, 2024

Request a free trial

✓ Valid
* Indicates required field

Your privacy is of utmost importance to us, your data will be used solely for contact purposes

Completed

Your request has been sent successfully

Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site.

We also use third-party cookies that help us analyze how you use this website, store your preferences, and provide the content and advertisements that are relevant to you. These cookies will only be stored in your browser with your prior consent.

You can choose to enable or disable some or all of these cookies but disabling some of them may affect your browsing experience.

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Always Active

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Always Active

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Always Active

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Always Active

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.