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ESPnet: End-to-End Speech Processing Toolkit
Description
This paper introduces a new open source platform for end-to-end speech processing named ESPnet. ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts widely-used dynamic neural network toolkits, Chainer and PyTorch, as a main deep learning engine. ESPnet also follows the Kaldi ASR toolkit style for data processing, feature extraction/format, and recipes to provide a complete setup for speech recognition and other speech processing experiments. This paper explains a major architecture of this software platform, several important functionalities, which differentiate ESPnet from other open source ASR toolkits, and experimental results with major ASR benchmarks.
Journal
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- Interspeech 2018
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Interspeech 2018 2018-09-02
ISCA
- Tweet
Keywords
Details 詳細情報について
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- CRID
- 1361137046164681216
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- Data Source
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- Crossref
- OpenAIRE