CoVoST 2 and Massively Multilingual Speech-to-Text Translation

Abstract

Speech translation has recently become an increasingly popular topic of research, partly due to the development of benchmark datasets. Nevertheless, current datasets cover a limited number of languages. With the aim to foster research in massive multilingual speech translation and speech translation for low resource language pairs, we release CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. This represents the largest open dataset available to date from total volume and language coverage perspective. Data sanity checks provide evidence about the quality of the data, which is released under CC0 license. We also provide extensive speech recognition, bilingual and multilingual machine translation and speech translation baselines with open-source implementation.

References in corpus (4)

• SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
• Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges
• End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
• Listen and Translate: A Proof of Concept for End-to-End Speech-to-Text Translation

Cited by in corpus (12)

• fairseq S2T: Fast Speech-to-Text Modeling with fairseq
• SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training
• Multilingual Speech Translation with Efficient Finetuning of Pretrained Models
• Large-Scale Self- and Semi-Supervised Learning for Speech Translation
• Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translation
• An Approach to Improve Robustness of NLP Systems against ASR Errors
• BSTC: A Large-Scale Chinese-English Speech Translation Dataset
• Searchable Hidden Intermediates for End-to-End Models of Decomposable Sequence Tasks
• LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
• Modular Speech-to-Text Translation for Zero-Shot Cross-Modal Transfer
• Do We Still Need Automatic Speech Recognition for Spoken Language Understanding?
• Zero-shot Speech Translation