{"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/leveraging-pre-trained-acoustic-feature","title":"Leveraging Pre-Trained Acoustic Feature Extractor For Affective Vocal Bursts Tasks","arxiv_id":null,"date":"2022-12-21","proceeding":"APSIPA 2022 12","authors":["Bagus Tris Atmaja","Akira Sasou"],"abstract":"Understanding humans’ emotions is a challenge for computers. Nowadays, research on speech emotion recognition has been conducted progressively. Instead of a speech, affective information may lay on short vocal bursts (i.e., cry when sad). In this study, we evaluated a recent self-supervised learning model to extract acoustic embedding for affective vocal bursts tasks. There are four tasks investigated on both regression and classification problems. Using similar architectures, we found the effectiveness of using a pre-trained model over the baseline methods. The study is further expanded to evaluate the different number of seeds, patiences, and batch sizes on the performance of the four tasks.","url_abs":"https://ieeexplore.ieee.org/document/9980083","url_pdf":"http://www.apsipa.org/proceedings/2022/APSIPA%202022/ThAM1-3/1570839332.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":"leveraging-pre-trained-acoustic-feature","repo_url":"https://github.com/bagustris/a-vb2022","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"},{"task_slug":"speech-emotion-recognition","task_name":"Speech Emotion Recognition"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}