Google Uses Neural Networks to Translate Without Transcribing

Google Uses Neural Networks to Translate Without Transcribing

Published By: New Scientist, 4/4/2017

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Researchers at Google Brain are developing a method to translate speech in one language to text in a different language, using neural networks. They hope to improve over more conventional automatic methods, where the speech is transcribed into written text, and then the written text is translated. The older method can be cumbersome, and initial experiments show that direct speech-to-text translation seems less subject to error. The new method could especially help speakers of rare languages communicate with others around the globe.

Flesch-Kincaid Grade Level of Article: 12.6

Extended Discussion Questions

  • If an app were created and released using this speech-to-text translation technology, how might you be able to use it? At home, for school, around town…?
  • Commentator Sharon Goldwater suggested in the article that such translation software could have been used to translate Haitian Creole after the 2010 earthquake in Haiti, had it been available. Besides disaster relief efforts, can you think of other situations where this technology could be applied?
  • In a high-stakes situations like disaster relief, what are some of the advantages of hiring human translators? What are some of the advantages of implementing a machine translation system?

Global Impact Learning Objectives:

  • LO 7.1.1 Explain how computing innovations affect communication, interaction, and cognition.
  • LO 7.1.2 Explain how people participate in a problem-solving process that scales

Global Impact Essential Knowledge:

  • EK 7.1.2D Human capabilities are enhanced by digitally enabled collaboration.
  • EK 7.1.2E Some online services use the contributions of many people to benefit both individuals and society.

Other CSP Big Ideas:

  • Idea 4 Algorithms

Banner Image:Network Visualization – Violet – Offset Crop“, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0.

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