preprint
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ESPnet-ST: All-in-One Speech Translation Toolkit
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- Citations
- 9
- References
- 47
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Paper overview
Öz
We present ESPnet-ST, which is designed for the quick development of speech-to-speech translation systems in a single framework. ESPnet-ST is a new project inside end-to-end speech processing toolkit, ESPnet, which integrates or newly implements automatic speech recognition, machine translation, and text-to-speech functions for speech translation. We provide all-in-one recipes including data pre-processing, feature extraction, training, and decoding pipelines for a wide range of benchmark datasets. Our reproducible results can match or even outperform the current state-of-the-art performances; these pre-trained models are downloadable. The toolkit is publicly available at https://github.com/espnet/espnet.
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Publication details
- DOI
- 10.48550/arxiv.2004.10234
- OpenAlex
- W3017650141
- Document type
- preprint
- Language
- EN
- Source
- arXiv (Cornell University)
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