Substitute Voice Production: Quantification of PE Segment Vibrations Using a Biomechanical Model
| Autor: | U. Eysholdt, Maria Schuster, Georg Luegmair, Björn Hüttner, Ercan Gürlek, Joerg Lohscheller, Michael Döllinger, R. Schwarz |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Male
Computer science Speech recognition Video Recording Biomedical Engineering Laryngectomy Models Biological Vibration Esophagus Phonation medicine Humans Voice rehabilitation business.industry Pharynx Signal Processing Computer-Assisted Pattern recognition Middle Aged Voice production Biomechanical Phenomena medicine.anatomical_structure Voice Biomechanical model Artificial intelligence Larynx Artificial business |
| Zdroj: | IEEE Transactions on Biomedical Engineering. 58:2767-2776 |
| ISSN: | 1558-2531 0018-9294 |
| DOI: | 10.1109/tbme.2011.2151860 |
| Popis: | After total larynx excision due to laryngeal cancer, the tracheoesophageal substitute tissue vibrations at the intersection between the pharynx and the esophagus [pharyngoesophageal segment (PE segment)] serve as voice generator. The quality of the substitute voice significantly depends on the vibratory characteristics of the PE segment. For improving voice rehabilitation, the relationship between the PE dynamics and the resulting substitute voice quality is a matter of particular interest. Precondition for a comprehensive analysis of this relationship is an objective quantification of the PE vibrations. For quantification purposes, a method is proposed, which is based on the reproduction of the tissue vibrations by means of a biomechanical model of the PE segment. An optimization procedure for an automatic determination of appropriate model parameters is suggested to adapt the model dynamics to tissue movements extracted from high-speed (HS) videos. The applicability of the optimization procedure is evaluated with ten synthetic data sets. A mean error of 8.2% for the determination of previously defined model parameters was achieved as well as an overall stability of 7.1%. The application of the model to six HS recordings presented a mean correlation of the vibration patterns of 82%. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|