Automatic Posture Evaluation for Profess onal Voice Users


Demirel C., Aydan H. C. , Kocak I., İnce G.

3rd International Conference on Computer Science and Engineering (UBMK), Sarajevo, Bosnia And Herzegovina, 20 - 23 September 2018, pp.318-323 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Sarajevo
  • Country: Bosnia And Herzegovina
  • Page Numbers: pp.318-323

Abstract

Voice trainings are executed mostly by therapists to their knowledge, experiences and skills. In these therapies, tension spots of a body are evaluated. A body is relieved with guidance of a therapist and physical exercises. However, voice quality evaluation of professional voice users are implemented subjectively. Classical voice evaluations can not be done by an objective approach, yet done with therapists' intuition. In this study, a measurement system was proposed to evaluate voice quality objectively by using the posture of a patient. Different machine learning algorithms were used to classify objective voice quality and posture quality, yet Artificial Neural Network models were found as best classifiers. Two models were tested using individual test sets and accuracies of voice quality and posture quality estimations were found to be 83.35% and 78.27%.