The aim of the research work presented is an automatic singing voice quality/type recognition system. For this purpose a database containing singers’ sample recordings is constructed and parameters are extracted from recorded voices of trained and untrained singers of different voice types. Parameters, which are especially designed for the analysis of the singing voice, are analyzed and a feature vector is formed. Each of singers’ voice samples is judged by experts and information about voice type/quality is obtained. Parameters extracted are used in the training process of a neural network and the effectiveness of an automatic voice timbre/quality classification is tested by comparing automatic recognition results with subjective expert judgements. Finally, discussion of results is presented and conclusions are derived.
(See document for exact affiliation information.)
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member Join the AES. If you need to check your member status, login to the Member Portal.
