Development of a femininity estimator using speaker recognition techniques for voice therapy of gender identity disorder clients

This paper describes the development of an estimator of perceptual femininity (PF) of an input utterance using speaker recognition techniques. The estimator was designed for its clinical use and the target speakers are Gender Identity Disorder (GID) clients, especially MtF (Male to Female) transsexuals. The voice therapy for MtFs is composed of three kinds of training; 1) raising the baseline F-0 range, 2) changing the baseline voice quality, and 3) enhancing F-0 dynamics to produce an exaggerated intonation pattern. The first two focus on static acoustic properties of speech and the voice quality is mainly controlled by size and shape of the articulators, which can be acoustically characterized by the spectral envelope. Gaussian Mixture Models (GMM) of F-0 values and spectrums were built separately for biologically male speakers and female ones. Using the four models, PF was estimated automatically for each of 142 utterances of 111 MtFs. The estimated values were compared with the PF values obtained through listening tests. Results showed very high correlation (R=0.86), which is comparable to the intra-rater correlation.