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CS-Dialogue: A 104-Hour Dataset of Spontaneous Mandarin-English Code-Switching Dialogues for Speech Recognition
Introduction
CS-Dialogue is a large-scale, publicly available Mandarin-English code-switching speech dialogue dataset. This dataset solves key problems found in existing code-switching speech datasets β mainly their small size, lack of natural conversations, and missing full-length dialogue recordings. It provides a solid foundation for advancing research in code-switching ASR and other related fields. The dataset is released under a CC BY-NC-SA 4.0 license, meaning it is available for non-commercial use.
Dataset Details
This dataset contains 104.02 hours of spontaneous dialogue recordings, consisting of 100 pairs of two-person conversations recorded by 200 speakers. Key features of the dataset include:
- Speakers: 200 speakers with strong English proficiency (e.g., IELTS β₯ 6 or passing TEM-4).
- Geographic Diversity: Speakers come from 30 provincial-level regions across mainland China.
- Content: Each conversation covers 2 to 6 topics and includes Mandarin-only, code-switching, and English-only segments.
- Audio Format: WAV files with a 16kHz sampling rate.
- Transcriptions: Carefully crafted, character-level manual transcriptions.
- Annotations: The dataset includes annotations for each utterance, and for the speakers level.
- Utterance-level:
id
,audio
(file path),text
(transcription). - Speaker-level:
speaker_id
,age
,gender
,location
(province),device
.
- Utterance-level:
Dataset Structure
The dataset file structure is as follows.
data
βββ long_wav/*.tar.gz
βββ short_wav/*.tar.gz
βββ index
βββ long_wav
β βββ dev.txt
β βββ test.txt
β βββ train.txt
βββ short_wav
β βββ dev
β β βββ text
β β βββ wav.scp
β βββ test
β β βββ text
β β βββ wav.scp
β βββ train
β βββ text
β βββ wav.scp
βββ total_infomation
βββ Information_Index.txt
For more details, please refer to our paper CS-Dialogue.
π Cite me
@article{zhou2025cs,
title={CS-Dialogue: A 104-Hour Dataset of Spontaneous Mandarin-English Code-Switching Dialogues for Speech Recognition},
author={Zhou, Jiaming and Guo, Yujie and Zhao, Shiwan and Sun, Haoqin and Wang, Hui and He, Jiabei and Kong, Aobo and Wang, Shiyao and Yang, Xi and Wang, Yequan and others},
journal={arXiv preprint arXiv:2502.18913},
year={2025}
}
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