%0 Journal Article
%T Noise Robust Acoustic Model Research Based on PMC<br>基于PMC方法的鲁棒声学模型研究
%A Zhang Ming-xin
%A Ni Hong
%A Zhang Dong-bin
%A Chen Guo-ping
%A <br>张明新
%A 倪宏
%A 张东滨
%A 陈国平
%J 中国科学院研究生院学报
%D 2006
%I 
%X In noise robust speech recognition, for PMC (parallel model combination) method, the performance of the combined model can approach that of the model matching the noisy environment theoretically, so it is an important noise robust speech recognition research field. In this paper, a novel feature MFCC_FWD_BWD, which is based on forward-backward difference dynamic parameters, is presented to satisfy the requirement that the feature construction matrix is invertible for PMC. On this condition, a novel structure model named parallel sub-state hidden Markov model (PSSHMM) is presented for PMC and each state of this model has parallel sub-states with transitions. In experiment, PSSHMM achieves good results under each kinds of noise and each levels of SNR, especially for non-stationary noise, its robust performance is also excellent.
%K parallel sub-state
%K speech recognition
%K noise robust
%K PMC<br>并行子状态
%K 语音识别
%K 噪声鲁棒
%K 并行模型结合
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=67CDFDECD959936E166E0F72DE972847&aid=60FB19A2760347FE&yid=37904DC365DD7266&vid=EA389574707BDED3&iid=94C357A881DFC066&sid=36C49E1242CC2C7A&eid=66D0A4667FE1A38D&journal_id=1002-1175&journal_name=中国科学院研究生院学报&referenced_num=0&reference_num=8