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

Holy Lovenia, Samuel Cahyawijaya, Genta Winata, Peng Xu, Yan Xu, Zihan Liu, Rita Frieske, Tiezheng Yu, Wenliang Dai, Elham J. Barezi, Qifeng Chen, Xiaojuan Ma, Bertram Shi, Pascale Fung


Abstract
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.
Anthology ID:
2022.lrec-1.788
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
7259–7268
Language:
URL:
https://aclanthology.org/2022.lrec-1.788
DOI:
Bibkey:
Cite (ACL):
Holy Lovenia, Samuel Cahyawijaya, Genta Winata, Peng Xu, Yan Xu, Zihan Liu, Rita Frieske, Tiezheng Yu, Wenliang Dai, Elham J. Barezi, Qifeng Chen, Xiaojuan Ma, Bertram Shi, and Pascale Fung. 2022. ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 7259–7268, Marseille, France. European Language Resources Association.
Cite (Informal):
ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation (Lovenia et al., LREC 2022)
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PDF:
https://preview.aclanthology.org/auto-file-uploads/2022.lrec-1.788.pdf
Code
 HLTCHKUST/ASCEND
Data
ASCEND