Recently, multilingual artificial intelligence assistants, exemplified by
ChatGPT, have gained immense popularity. As a crucial gateway to human-computer
interaction, multilingual automatic speech recognition (ASR) has also garnered
significant attention, as evidenced by systems like Whisper. However, the
proprietary nature of the training data has impeded researchers' efforts to
study multilingual ASR. This paper introduces MSR-86K, an evolving, large-scale
multilingual corpus for speech recognition research. The corpus is derived from
publicly accessible videos on YouTube, comprising 15 languages and a total of
86,300 hours of transcribed ASR data. We also introduce how to use the MSR-86K
corpus and other open-source corpora to train a robust multilingual ASR model
that is competitive with Whisper. MSR-86K will be publicly released on
HuggingFace, and we believe that such a large corpus will pave new avenues for
research in multilingual ASR.

该论文介绍了 MSR-86K，这是一个逐渐增长的大规模多语言语音识别研究语料库，由 YouTube 上公开可访问的视频转录数据组成，包括 15 种语言和总共 86300 小时的 ASR 数据。同时，该论文还介绍了如何使用 MSR-86K 语料库和其他开源语料库来训练一个与 Whisper 相媲美的强大的多语言语音识别模型。我们将在 HuggingFace 上公开发布 MSR-86K，相信这样一个大规模的语料库将为多语言语音识别的研究开辟新的道路。