International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA 1999)
Voice registers are widely affected when voice diseases appear. These diseases have to be
treated during an early stage. Detection of voice diseases may be carried out by means of acoustic
analysis of voice register. Many algorithms to calculate acoustic parameters have been developed and
have been demonstrated that there is a great correlation between parameter deviations and
The effectiveness and importance of the acoustic analysis of pathological voices have been proven by many experimental researches which demonstrate that acoustic parameters of pathological voices are deviated from the mean. So, voice registers can be vector quantified in order to classify into healthy and impaired voices.
It is well known that male and female voices have different acoustic properties. Due to this fact, we may think that feature gender has to be kept in mind as a new feature in order to detect voice impairment from the voice register alone.
The aim of this paper is to study the influence of the feature gender to carry out classification and automatic detection of voice diseases.
Bibliographic reference. Godino-Llorente, Juan I. / Aguilera-Navarro, Santiago / Palazuelos-Cagigas, Sira E. / Martin-Sánchez, José L. (1999): "Does it affect feature "sex" on automatic detection of impaired voices?", In MAVEBA-1999, 48-53.