@InProceedings{SampaioJack:2017:VoTrMo,
               author = "Sampaio, Rafael de Assuncao and Jackowski, Marcel Parolin",
          affiliation = "Institute of Mathematics and Statistics, University of Sao Paulo 
                         and Institute of Mathematics and Statistics, University of Sao 
                         Paulo",
                title = "Vocal tract morphology using real-time magnetic resonance 
                         imaging",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "level set, active contours, morphology, vocal tract, magnetic 
                         resonance imaging.",
             abstract = "Real-time Magnetic Resonance Imaging (rtMRI) leads to the dynamic 
                         observation of hidden processes of articulation in an 
                         unprecedented way. The non-invasive image acquisition nature of 
                         MRI combined with enhanced anatomical discrimination made rtMRI 
                         the reference in capturing vocal tract configurations during 
                         speech production. However, this development also unveiled 
                         challenges, such as the shape extraction and analysis of the vocal 
                         tract contours automatically. This work describes automated 
                         techniques for the segmentation of the vocal tract and 
                         identification of articulatory structures using rtMRI. The 
                         identification of these structures is vital for modeling 
                         articulatory synthesis. The methodology is based on level set 
                         methods to outline the vocal tract shape. Changes in the vocal 
                         tract shape and its structures were investigated for different 
                         corpora in order to bind the expression of phonemes and the 
                         behavior of the anatomical shapes. These shapes were labeled from 
                         basal form invariants, whose final evolution yielded the 
                         classification of regions of interest. The methodology resulting 
                         from this work may be employed in accent-suppression systems, 
                         speech production for laryngectomized patients, and therapetic 
                         techniques for children suffering from speech apraxia.",
  conference-location = "Niter{\'o}i, RJ, Brazil",
      conference-year = "17-20 Oct. 2017",
                  doi = "10.1109/SIBGRAPI.2017.54",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2017.54",
             language = "en",
                  ibi = "8JMKD3MGPAW/3PFRMML",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3PFRMML",
           targetfile = "PID4960363.pdf",
        urlaccessdate = "2024, May 02"
}