机器翻译辅助的中蒙、维汉语音翻译数据集子集

Abstract

At present, there are few public datasets for speech translation, especially those between Chinese and other low-resource languages. The development of end-to-end speech translation is limited by resources. In light of the research idea of international speech translation datasets, in this paper, we used the public speech recognition datasets (AISHELL and THUYG-20) to convert them into speech translation datasets through machine translation. After data processing, they were reviewed and verified by experts, so as to obtain high-quality speech translation datasets. The dataset includes Chinese-Mongolian speech translation dataset and Uygur-Chinese speech translation dataset, and the audio sampling rate is 16 kHz. The Chinese-Mongolian speech translation subset contains 1,919 items with a size of 238 MB. The Uygur-Chinese speech translation subset contains 3,692 samples with a size of 652 MB. This dataset can be used for the research on end-to-end speech translation, and provide data support for exploring the speech translation between Chinese and minority languages. As the dataset has been reviewed and verified by experts, it can also be combined with speech recognition dataset to study machine translation.