  Previous research has found that voices can provide reliable information for
gender classification with a high level of accuracy. In social psychology,
perceived vocal masculinity and femininity has often been considered as an
important feature on social behaviours. While previous studies have
characterised acoustic features that contributed to perceivers' judgements of
speakers' vocal masculinity or femininity, there is limited research on
building an objective masculinity/femininity scoring model and characterizing
the independent acoustic factors that contribute to the judgements of speakers'
vocal masculinity or femininity. In this work, we firstly propose an objective
masculinity/femininity scoring system based on the Extreme Random Forest and
then characterize the independent and meaningful acoustic factors contributing
to perceivers' judgements by using a correlation matrix based hierarchical
clustering method. The results show the objective masculinity/femininity
ratings strongly correlated with the perceived masculinity/femininity ratings
when we used an optimal speech duration of 7 seconds, with a correlation
coefficient of up to .63 for females and .77 for males. 9 independent clusters
of acoustic measures were generated from our modelling of femininity judgements
for female voices and 8 clusters were found for masculinity judgements for male
voices. The results revealed that, for both sexes, the F0 mean is the most
critical acoustic measure affects the judgement of vocal masculinity and
femininity. The F3 mean, F4 mean and VTL estimators are found to be highly
inter-correlated and appeared in the same cluster, forming the second
significant factor. Next, F1 mean, F2 mean and F0 standard deviation are
independent factors that share similar importance. The voice perturbation
measures, including HNR, jitter and shimmer, are of lesser importance.
