{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/anno-mi-a-dataset-of-expert-annotated","title":"Anno-MI: A Dataset of Expert-Annotated Counselling Dialogues","arxiv_id":null,"date":"2022-04-27","proceeding":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022 4","authors":["Zixiu Wu","Simone Balloccu","Vivek Kumar","Rim Helaoui","Ehud Reiter","Diego Reforgiato Recupero","Daniele Riboni"],"abstract":"Research on natural language processing for counselling dialogue analysis has seen substantial development in recent years, but access to this area remains extremely limited due to the lack of publicly available expert-annotated therapy conversations. In this work, we introduce AnnoMI, the first publicly and freely accessible dataset of professionally transcribed and expert-annotated therapy dialogues. It consists of 133 conversations that demonstrate high- and low-quality motivational interviewing (MI), an effective counselling technique, and the annotations by domain experts cover key MI attributes. We detail the data collection process including dialogue selection, transcription and annotation. We also present analyses of AnnoMI and discuss its potential applications.","url_abs":"https://ieeexplore.ieee.org/document/9746035","url_pdf":"https://zixiu-alex-wu.github.io/files/AnnoMI_ICASSP_Camera_Ready_Personal_Use.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"anno-mi-a-dataset-of-expert-annotated","repo_url":"https://github.com/uccollab/AnnoMI","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"dialogue-generation","task_name":"Dialogue Generation"},{"task_slug":"natural-language-understanding","task_name":"Natural Language Understanding"}],"methods":[],"datasets_introduced":[{"slug":"annomi","name":"AnnoMI","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}