{"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/a-multilinear-tongue-model-derived-from","title":"A Multilinear Tongue Model Derived from Speech Related MRI Data of the Human Vocal Tract","arxiv_id":"1612.05005","date":"2016-12-15","proceeding":null,"authors":["Alexander Hewer","Stefanie Wuhrer","Ingmar Steiner","Korin Richmond"],"abstract":"We present a multilinear statistical model of the human tongue that captures\nanatomical and tongue pose related shape variations separately. The model is\nderived from 3D magnetic resonance imaging data of 11 speakers sustaining\nspeech related vocal tract configurations. The extraction is performed by using\na minimally supervised method that uses as basis an image segmentation approach\nand a template fitting technique. Furthermore, it uses image denoising to deal\nwith possibly corrupt data, palate surface information reconstruction to handle\npalatal tongue contacts, and a bootstrap strategy to refine the obtained\nshapes. Our evaluation concludes that limiting the degrees of freedom for the\nanatomical and speech related variations to 5 and 4, respectively, produces a\nmodel that can reliably register unknown data while avoiding overfitting\neffects. Furthermore, we show that it can be used to generate a plausible\ntongue animation by tracking sparse motion capture data.","url_abs":"http://arxiv.org/abs/1612.05005v5","url_pdf":"http://arxiv.org/pdf/1612.05005v5.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":"a-multilinear-tongue-model-derived-from","repo_url":"https://github.com/m2ci-msp/mri-shape-framework","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"a-multilinear-tongue-model-derived-from","repo_url":"https://github.com/m2ci-msp/mri-shape-tools","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"denoising","task_name":"Denoising"},{"task_slug":"image-denoising","task_name":"Image Denoising"},{"task_slug":"image-segmentation","task_name":"Image Segmentation"},{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}