@article{oai:nitech.repo.nii.ac.jp:00005231,
 author = {Itaya, Yohei and Zen, Heiga and Nankaku, Yoshihiko and 南角, 吉彦 and Miyajima, Chiyomi and Tokuda, Keiichi and 徳田, 恵一 and Kitamura, Tadashi},
 issue = {3},
 journal = {IEICE transactions on information and systems},
 month = {Mar},
 note = {This paper investigates the effectiveness of the DAEM (Deterministic Annealing EM) algorithm in acoustic modeling for speaker and speech recognition. Although the EM algorithm has been widely used to approximate the ML estimates, it has the problem of initialization dependence. To relax this problem, the DAEM algorithm has been proposed and confirmed the effectiveness in artificial small tasks. In this paper, we applied the DAEM algorithm to practical speech recognition tasks: speaker recognition based on GMMs and continuous speech recognition based on HMMs. Experimental results show that the DAEM algorithm can improve the recognition performance as compared to the standard EM algorithm with conventional initialization algorithms, especially in the flat start training for continuous speech recognition., application/pdf},
 pages = {425--431},
 title = {Deterministic Annealing EM Algorithm in Acoustic Modeling for Speaker and Speech Recognition},
 volume = {E88-D},
 year = {2005},
 yomi = {ナンカク, ヨシヒコ and トクダ, ケイイチ}
}