Multi-Information Model Fused Framework for Chinese Dialect Identification

Abstract

This paper presents a model fused approach to Chinese dialect identification by combining multi-information including acoustic, phonotactic and prosodic feature. At first we analyze the way to translate language information into these features, and then propose a model fused framework for back-end classification. The experimental results show that the proposed method improves identification performance greatly and the prosodic features are more effective for shorter speech.