preprintarXiv (Cornell University)Dec 8, 2015GREEN OA

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

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Abstract

We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages. Because it replaces entire pipelines of hand-engineered components with neural networks, end-to-end learning allows us to handle a diverse variety of speech including noisy environments, accents and different languages. Key to our approach is our application of HPC techniques, resulting in a 7x speedup over our previous system. Because of this efficiency, experiments that previously took weeks now run in days. This enables us to iterate more quickly to identify superior architectures and algorithms. As a result, in several cases, our system is competitive with…

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2,179
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Authors

34

Topics & keywords

Keywords
  • Computer science
  • End-to-end principle
  • Mandarin Chinese
  • Speedup
  • Speech recognition
  • Latency (audio)
  • Low latency (capital markets)
  • Variety (cybernetics)
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