%0 Journal Article
%T Stream weight optimization method of multi stream HMMs<br>多数据流隐马尔可夫模型的流权值优化方法*
%A QIN Wei
%A WEI Gang
%A <br>秦伟
%A 韦岗
%J 计算机应用研究
%D 2007
%I 
%X This paper proposed a novel stream-weight optimization method based on the likelihood-ration maximization criterion and the N-best algorithm. The proposed method had advantages that not only computational complexity was significantly reduced, but also audio-visual speech recognition performance was significantly improved by using a small optimization data set. Further experimental results demonstrate that the audio-visual speech recognition system provides significant enhancement of robustness in noisy environments.
%K audio-visual speech recognition
%K likelihood-ratio maximization criterion
%K stream weight<br>双模语音识别
%K 似然比最大化准则
%K 流权值
%K 多数据流
%K 隐马尔可夫模型
%K 权值
%K 优化方法
%K HMMs
%K method
%K of
%K 识别率
%K 语音识别系统
%K 视频
%K 合音
%K 方法优化
%K 利用
%K 信噪比
%K 条件
%K 量优化
%K 实验
%K 算法
%K 准则
%K 大化
%K 似然比
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=C793235A4E87B8F6EEE9EF08DB53D074&yid=A732AF04DDA03BB3&vid=B91E8C6D6FE990DB&iid=708DD6B15D2464E8&sid=8C83C265AD318E34&eid=331211A5F5616413&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12