COAS2W: A Chinese Older-Adults Spoken-to-Written Transformation Corpus with Context Awareness

ACL ARR 2025 May Submission2100 Authors

Abstract: Spoken language from older adults often deviates from written norms due to omission, disordered syntax, constituent errors, and redundancy, limiting the usefulness of automatic transcripts in downstream tasks. We present COAS2W, a Chinese spoken-to-written corpus of 10, 004 utterances from older adults, each paired with a written version, fine-grained error labels, and four-sentence context. Unlike existing resources, COAS2W captures cross-sentence dependencies crucial for resolving ambiguities and recovering missing content. Fine-tuned lightweight open-source models on COAS2W outperform larger closed-source models. Context ablation shows the value of multi-sentence input, and normalization improves performance on downstream translation tasks. COAS2W supports the development of inclusive, context-aware language technologies for older speakers.

Paper Type: Long

Research Area: Speech Recognition, Text-to-Speech and Spoken Language Understanding

Research Area Keywords: spoken language understanding

Contribution Types: Data resources

Languages Studied: Chinese

Submission Number: 2100