Abstract
The study of human singing has focused extensively on the analysis of voice characteristics. At the same time, a substantial body of work has been under study aimed at modeling and synthesizing the human voice. The work on which we report brings together some key analysis and synthesis principles to create a new model for digitally improving the perceived quality of an average singing voice. The model presented employs an analysis‐by‐synthesis overlap‐add (ABS‐OLA) sinusoidal model, which in the past has been used for the analysis and synthesis of speech, in combination with a spectral model of the vocal tract. The ABS‐OLA sinusoidal model for speech has been shown to be a flexible, accurate, and computationally efficient representation capable of producing a natural‐sounding singing voice [E. B. George and M. J. T. Smith, Trans. Speech Audio Processing 5, 389–406 (1997)]. A spectral model infused in the ABS‐OLA uses Generalized Gaussian functions to provide a simple framework which enables the precise modification of spectral characteristics while maintaining the quality and naturalness of the original voice. Furthermore, it is shown that the parameters of the new ABS‐OLA can accommodate pitch corrections and vocal quality enhancements while preserving naturalness and singer identity. Examples of enhanced country singing will be presented.
Published Version
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