Within this paper, the authors report on an experiment on automatic labelling of perceived voice roughness (R) and breathiness (B), according to the GRBAS scale. The main objective of the experiment has not been to correlate objective measures to perceived R and B, but to automatically evaluate R and B. For this purpose, a system has been trained that extracts the first mel-frequency cepstral coefficients (MFCC) of available sustained vowel phonations. Afterwards, a classifier has been trained to estimate the corresponding degrees of roughness and breathiness. The obtained results reveal a significant correlation between subjective and automatic labelling, hence indicating the feasibility of objective evaluation of voice quality by means of perceptually meaningful measures.
Abstract. It is well known that many neurological diseases leave a fingerprint in voice and speech production. The dramatic impact of these pathologies in life quality is a growing concert. Many techniques have been designed for the detection, diagnose and monitoring the neurological disease. Most of them are costly or difncult to extend to primary services. The present paper shows that some neurological diseases can be traced a the level of voice production. The detection procedure would be based on a simple voice test. The availability of advanced tools and methodologies to monitor the organic pathology of voice would facilí-tate the implantation of these tests. The paper hypothesizes some of the underlying mechanisms affecting the production of voice and presents a general description of the methodological foundations for the voice analysis system which can estímate correlates to the neurological disease. A case of study is presented from spasmodic dysphonia to ¡Ilústrate the possibilities of the methodology to monitor other neurological problems as well.
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