LLMs for automatic annotation of Mandarin narrative transcripts

ArXi:2605.17205v1 Announce Type: new Linguistic annotation of transcribed speech is essential for research in language acquisition, language disorders, and sociolinguistics, yet remains labor-intensive and time-consuming. While Large Language Models (LLMs) have shown promise in automating annotation tasks, their ability to handle complex dis