Multidimensional analysis of vocal female classification

• Grant number: 10/11875-0
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: December 01, 2010
• End date: November 30, 2013
• Field of knowledge: Linguistics, Literature and Arts - Arts - Music
• Principal Investigator: Lílian Neto Aguiar Ricz
• Grantee: Snizhana Drahan
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil

Abstract

To perform a vocal classification is necessary exams of tessitura, transition notes and ease for a particular register, but still sometimes doubts arise. Currently it is not so rare to find discussions on the apprentices voice classification between the singing student and his teacher, even among singing teachers. The task of this project is to verify that the modern technology, computer programs and imaging technology equipment can help in the vocal female classification. It is believed that the singing female voice evaluation, through physiological and acoustic analysis comparison, may not only allow the confirmation that such resources can be used for the vocal classification, but also to avoid possible vocal errors of training. The hypothesis of this research is that in the voices evaluation for female singers will present the same vocal classification, both for analytic listening as for computerized acoustic analysis and larynx physiological dynamic image (videofluoroscopy). For the research will be used 60 singers recruited from the Department of Music of the ECA-USP in Ribeirão Preto and region coral's singers, which have stable notions of vocal technique. The voices of the singers will go through series of assessments - analytic listening, vocal range and laryngeal position - through the program Sonar ® and Equipment Philips ®-BV Pulsera associated with the recording device from Philips ® images MDVDR-100-Medical DVD Recorder. The results will be analyzed and correlated statistically using the Shapiro-Wilks test and the relationships between categorical and continuous variables, the t-test or ANOVA as the amount of levels of categorical variables.