%0 Journal Article
%T Study on audio classification based on 1-state HMM<br>基于单状态HMM的音频分类方法研究
%A ZHENG Ji-ming
%A LI Rui-xian
%A PU Xing-chengInstitute of applied mathematics
%A Chongqing University of Posts
%A Telecommunications
%A Chongqing
%A China
%A College of Computer Science
%A Technology
%A <br>郑继明
%A 李瑞仙
%A 蒲兴成
%J 计算机应用
%D 2009
%I 
%X Hidden markov model (HMM),based on statistical signal, plays an important role in content-based audio retrieval system. According to the characteristic that pays more attention to the type than to content of audio classification, 1-state HMM was used for audio classification, which overcame the shortcoming of assumption of multi-state HMM model's initial state probabilities and state transition probabilities in the course of model-initializing. The experiment shows the method for audio classification based on 1-state HMM could decrease the misrecognition effectively and increase the accuracy of audio classification.
%K Hidden Markov Model (HMM)
%K audio classification
%K 1-state<br>隐马尔可夫模型
%K 音频分类
%K 单状态
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=F30E4F8CE4D0EEC20587384DE11810CE&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=0B39A22176CE99FB&sid=5A735990D5DE8BF4&eid=0BD4FAD4A90498AB&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=11