Voice-Based Gender Identification in Multimedia Applications

摘要

In the context of content-based multimedia indexing gender identification based on speech signal is an important task. In this paper a set of acoustic and pitch features along with different classifiers are compared for the problem of gender identification. We show that the fusion of features and classifiers performs better than any individual classifier. Based on such conclusions we built a system for gender identification in multimedia applications. The system uses a set of Neural Networks with acoustic and Pitch related features.