@inproceedings{zhou-etal-2026-childtalk,
    title = "{C}hild{T}alk: A Multi-Dialect {C}hinese Child Speech Corpus with Full-Length Child{--}Caregiver Conversations for Speech Recognition",
    author = "Zhou, Jiaming  and
      Guo, Yujie  and
      Zhao, Shiwan  and
      Lu, Yao  and
      Wang, Jianye  and
      Sun, Haoqin  and
      Wang, Hui  and
      Qin, Yong",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.251/",
    pages = "5103--5116",
    ISBN = "979-8-89176-395-1",
    abstract = "Automatic speech recognition (ASR) for children remains challenging due to developmental variability and the scarcity of high-quality corpora, especially for Mandarin and its dialects. In this paper, we present ChildTalk, a large-scale Chinese child speech corpus designed to address this gap. It contains 112.5 hours of speech from 498 children (aged 2{--}8) and 500 caregivers, recorded as natural child{--}caregiver conversations. Unlike prior Mandarin child ASR corpora that mainly release isolated utterances, ChildTalk provides full-length dialogues with complete transcriptions, preserving turn-taking and discourse context. To our knowledge, it is the first publicly available Mandarin child speech corpus with full-length dialogues and systematic coverage of standard Mandarin, eight Mandarin dialect subgroups, and two additional dialects (Southern Min and Jin). We benchmark end-to-end models trained from scratch, large pre-trained ASR models fine-tuned on ChildTalk, omni-modal LLMs in a zero-shot setting, and commercial speech transcription APIs. Fine-tuning on ChildTalk consistently improves both in-domain and cross-domain performance. These results indicate that ChildTalk provides a challenging, broad-coverage testbed for Chinese child ASR, dialect robustness, and dialogue-level modeling. The dataset will be made freely available for all academic purposes."
}