摘要
Baum- Welch算法是在语音领域中用于 HMM( hidden Markov model)模型参数训练的最基本方法之一 .但它在多样本训练时存在着严重的上、下溢问题 ,需要不断地人工介入来调整中间参数 .该文提出了一种新的能消除上、下溢问题的 Baum- Welch改进算法 .该算法不但摆脱了人工介入 ,保证了计算的精度 ,而且不会带来过大的计算和存储要求 .
Baum Welch algorithm, which is often troubled with overflow, is one of the basic methods in the field of speech signal processing. People have to adjust the inner parameters constantly. So in this paper, a modified Baum Welch algorithm is presented to avoid the overflow completely. With this algorithm manual adjustment is not needed and the computation accuracy is guaranteed. There is no significant extra cost of computation and storage. The feasibility of the new algorithm is shown in the experiment.
出处
《软件学报》
EI
CSCD
北大核心
2000年第5期707-710,共4页
Journal of Software
基金
国家自然科学基金!(No.69982005)资助
