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Code-switching is a speech phenomenon occurring when a speaker switcheslanguage during a conversation. Despite the spontaneous nature ofcode-switching in conversational spoken language, most existing works collectcode-switching data from read speech instead of spontaneous speech. ASCEND (ASpontaneous Chinese-English Dataset) is a high-quality Mandarin Chinese-Englishcode-switching corpus built on spontaneous multi-turn conversational dialoguesources collected in Hong Kong. We report ASCEND's design and procedure forcollecting the speech data, including annotations. ASCEND consists of 10.62hours of clean speech, collected from 23 bilingual speakers of Chinese andEnglish. Furthermore, we conduct baseline experiments using pre-trained wav2vec2.0 models, achieving a best performance of 22.69\% character error rate and27.05% mixed error rate.

ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation