The invention discloses a personalized HRTF generation method based on spectrum
feature extraction and clustering analysis, and belongs to the technical field of three-dimensional audio, the method comprises two parts of
feature extraction and feature clustering analysis on an HRTF spectrum, and the method comprises the following steps: firstly, loading and pre-
processing input sofa data, hilbert transform and a cross-
correlation function are used to acquire a binaural
time difference ITD, an amplitude difference is calculated to acquire a binaural
sound intensity difference ILD, sub-band division of an equivalent matrix bandwidth is used to determine a
center frequency, direction
transfer function data DTF is acquired through a designed
Gammatone filter, positive gradient information is calculated, and finally, a relation matrix and a clustering center are acquired through features, so that the clustering accuracy is improved. And carrying out dimension reduction mapping by using MDS, and obtaining a clustering result and a clustering center by using an
algorithm to realize three-dimensional
sound field rendering. The method is not limited by the
audiometry environment of the user, the personalized HRTF of the user is autonomously, conveniently and quickly matched, accurate positioning is achieved,
confusion is reduced, and the method can be popularized and used in scenes such as
virtual reality and games.