Code-switching is a speech phenomenon occurring when a speaker switches
language during a conversation. Despite the spontaneous nature of
code-switching in conversational spoken language, most existing works collect
code-switching data from read speech instead of spontaneous speech. ASCEND (A
Spontaneous Chinese-English Dataset) is a high-quality Mandarin Chinese-English
code-switching corpus built on spontaneous multi-turn conversational dialogue
sources collected in Hong Kong. We report ASCEND's design and procedure for
collecting the speech data, including annotations. ASCEND consists of 10.62
hours of clean speech, collected from 23 bilingual speakers of Chinese and
English. Furthermore, we conduct baseline experiments using pre-trained wav2vec
2.0 models, achieving a best performance of 22.69\% character error rate and
27.05% mixed error rate.

本研究报告了 ASCEND 计划的设计及数据采集方式，其中包括 10.62 小时的高质量普通话中英文语音，采用 wav2vec 2.0 模型进行基线实验，取得了 22.69% 的字符误差率和 27.05% 的混合误差率。