As one of the techniques enabling individual singers to produce the varieties of voice timbre beyond their own physical constraints, a statistical voice timbre control technique based on the perceived age has been developed. In this technique, the perceived age of a singing voice, which is the age of the singer as perceived by the listener, is used as one of the intuitively understandable measures to describe voice characteristics of the singing voice. The use of statistical voice conversion (SVC) with a singer-dependent multiple-regression Gaussian mixture model (MR-GMM), which effectively models the voice timbre variations caused by a change of the perceived age, makes it possible for individual singers to manipulate the perceived ages of their own singing voices while retaining their own singer identities. However, there still remain several issues; e.g., 1) a controllable range of the perceived age is limited; 2) quality of the converted singing voice is significantly degraded compared to that of a natural singing voice; and 3) each singer needs to sing the same phrase set as sung by a reference singer to develop the singer-dependent MR-GMM. To address these issues, we propose the following three methods; 1) a method using gender-dependent modeling to expand the controllable range of the perceived age; 2) a method using direct waveform modification based on spectrum differential to improve quality of the converted singing voice; and 3) a rapid unsupervised adaptation method based on maximum a posteriori (MAP) estimation to easily develop the singer-dependent MR-GMM. The experimental results show that the proposed methods achieve a wider controllable range of the perceived age, a significant quality improvement of the converted singing voice, and the development of the singer-dependnet MR-GMM using only a few arbitrary phrases as adaptation data.

The perceived age of a singing voice is the age of the singer as perceived by the listener, and is one of the notable characteristics that determines perceptions of a song. In this paper, we describe an investigation of acoustic features that have an effect on the perceived age, and a novel voice timbre control technique based on the perceived age for singing voice conversion (SVC). Singers can sing expressively by controlling prosody and voice timbre, but the varieties of voices that singers can produce are limited by physical constraints. Previous work has attempted to overcome this limitation through the use of statistical voice conversion. This technique makes it possible to convert singing voice timbre of an arbitrary source singer into those of an arbitrary target singer. However, it is still difficult to intuitively control singing voice characteristics by manipulating parameters corresponding to specific physical traits, such as gender and age. In this paper, we first perform an investigation of the factors that play a part in the listener's perception of the singer's age at first. Then, we applied a multiple-regression Gaussian mixture models (MR-GMM) to SVC for the purpose of controlling voice timbre based on the perceived age and we propose SVC based on the modified MR-GMM for manipulating the perceived age while maintaining singer's individuality. The experimental results show that 1) the perceived age of singing voices corresponds relatively well to the actual age of the singer, 2) prosodic features have a larger effect on the perceived age than spectral features, 3) the individuality of a singer is influenced more heavily by segmental features than prosodic features 4) the proposed voice timbre control method makes it possible to change the singer's perceived age while not having an adverse effect on the perceived individuality.