Word recognition by a parallel-branch subunit model based on misrecognized data in semi-continuous HMM

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作者：
Korea Advanced Inst of Technology, Taejon, Korea, Republic of [1 ]
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来源：
IEEE Signal Process Lett | / 3卷 / 66-68期
关键词：
Corrective initialization algorithm - Hidden Markov model - Parallel branch subunit model - Word recognition;
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摘要：
In this letter, we propose a parallel-branch subunit model in semicontinuous HMM for improved initialization and training in word recognition. In this method, we obtain the model by adding a new subunit branch based on misrecognized data in training to the previous parallel branches for that subunit. Simulation results show that this proposed model is efficient and gives good recognition performance in word recognition.
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