CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus
- URL: http://arxiv.org/abs/2002.01320v2
- Date: Tue, 9 Jun 2020 19:24:52 GMT
- Title: CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus
- Authors: Changhan Wang, Juan Pino, Anne Wu, Jiatao Gu
- Abstract summary: CoVoST is a multilingual speech-to-text translation corpus from 11 languages into English.
It diversified with over 11,000 speakers and over 60 accents.
CoVoST is released under CC0 license and free to use.
- Score: 57.641761472372814
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Spoken language translation has recently witnessed a resurgence in
popularity, thanks to the development of end-to-end models and the creation of
new corpora, such as Augmented LibriSpeech and MuST-C. Existing datasets
involve language pairs with English as a source language, involve very specific
domains or are low resource. We introduce CoVoST, a multilingual speech-to-text
translation corpus from 11 languages into English, diversified with over 11,000
speakers and over 60 accents. We describe the dataset creation methodology and
provide empirical evidence of the quality of the data. We also provide initial
benchmarks, including, to our knowledge, the first end-to-end many-to-one
multilingual models for spoken language translation. CoVoST is released under
CC0 license and free to use. We also provide additional evaluation data derived
from Tatoeba under CC licenses.
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