To bridge the semantic gap between audio feature and high-level semantic concept

an approach for semantic-audio content Analysis is presented in this paper.Hidden Markov model(HMM) is trained for modeling BE.In order to extract G_BE corresponding to a semantic window

Bayesian decision theory is used to eliminate the analysis window not belonging to any predefined HMM.Then

each of the residual analysis windows within the semantic window is classified to BE class by criterion of maximum Bayesian posterior probability.Ignoring the order and repetition of BE

G_BE is got.Logic definition of high level audio semantic concept is the connection of G_BE and HC

through which HC can be extracted.The experimental results demonstrate that the proposal approach could extract HC like human thoughts

and could bridge the semantic gap to some degree.