This paper introduces GigaST, a large-scale pseudo speech translation (ST) corpus. We create the corpus by translating the text in GigaSpeech, an English ASR corpus, into German and Chinese. The training set is translated by a strong machine translation system and the test set is translated by human. ST models trained with an addition of our corpus obtain new state-of-the-art results on the MuST-C English-German benchmark test set. We provide a detailed description of the translation process and verify its quality. We make the translated text data public and hope to facilitate research in speech translation. Additionally, we also release the training scripts on NeurST to make it easy to replicate our systems. GigaST dataset is available at https://st-benchmark.github.io/resources/GigaST.

翻译：本文介绍了GigaST，一个大规模伪语音翻译(ST)语料库。我们通过将英语自动语音识别(ASR)语料库GigaSpeech中的文本翻译成德语和中文来构建该语料库。训练集由强大的机器翻译系统翻译，测试集则由人工翻译。使用添加了本语料库进行训练的语音翻译模型在MuST-C英德基准测试集上取得了新的最先进结果。我们详细描述了翻译过程并验证了其质量。我们将翻译后的文本数据公开，希望推动语音翻译研究。此外，我们还在NeurST上发布了训练脚本，以便轻松复现我们的系统。GigaST数据集可通过https://st-benchmark.github.io/resources/GigaST获取。