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  1. Installing collected packages: google-cloud-translate Successfully installed google-cloud-translate-3.8.2 Now, you're ready to use the Translation API! Note: If you're setting up your own Python development environment, you can follow these guidelines .

  2. Sep 30, 2022 · The Translation API's recognition engine supports a wide variety of languages for the Neural Machine Translation (NMT) model. These languages are specified within a recognition request using language code parameters as noted on this page. Most language code parameters conform to ISO-639 identifiers, except where noted.

  3. Sep 30, 2022 · Before you can use Media Translation, you need to set up a Google Cloud project and enable the Media Translation API for that project. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and ...

  4. To help others better understand your language, you can submit feedback to Google Translate Contribute. We pay special attention to written languages used widely across the web, as well as languages with passionate contributors who can help make improvements to translation quality. Learn more about Google Translate Contribute.

  5. Google's service, offered free of charge, instantly translates words, phrases, and web pages between English and over 100 other languages.

  6. If your device has a microphone, you can translate spoken words and phrases. In some languages, you can hear the translation spoken aloud. Important: If you use an audible screen reader, we recommend you use headphones, as the screen reader voice may interfere with the transcribed speech. Translate by speech

  7. Sep 26, 2016 · Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, with the potential to overcome many of the weaknesses of conventional phrase-based translation systems. Unfortunately, NMT systems are known to be computationally expensive both in training and in translation inference. Also, most NMT systems have difficulty with rare words. These issues have ...

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