Automatic Generation of Non-uniform HMM Topologies Based on the MDL Criterion(Speech and Hearing)
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概要
- 論文の詳細を見る
We propose a new method to introduce the Minimum Description Length (MDL) criterion to the automatic generation of nonuniform, context-dependent HMM topologies. Phonetic decision tree clustering is widely used, based on the Maximum Likelihood (ML) criterion, and only creates contextual variations. However, the ML criterion needs to predetermine control parameters, such as the total number of states, empirically for use as stop criteria. Information criteria have been applied to solve this problem for decision tree clustering. However, decision tree clustering cannot create topologies with various state lengths automatically. Therefore, we propose a method that applies the MDL criterion as split and stop criteria to the Successive State Splitting (SSS) algorithm as a means of generating contextual and temporal variations. This proposed method, the MDL-SSS algorithm, can automatically create adequate topologies without such predetermined parameters. Experimental results for travel arrangement dialogs and lecture speech show that the MDL-SSS can automatically stop splitting and obtain more appropriate HMM topologies than the original one.
- 社団法人電子情報通信学会の論文
- 2004-08-01
著者
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Matsui T
Atr Spoken Language Translation Communication Laboratories
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Matsui T
Spoken Language Translation Research Laboratories Advanced Telecommunications Research Institute Int
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NAKAMURA Satoshi
Spoken Language Communication Group, Knowledge Creating Communication Research Center, National Inst
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Jitsuhiro T
Spoken Language Translation Research Laboratories Advanced Telecommunications Research Institute Int
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Jitsuhiro Takatoshi
Spoken Language Translation Research Laboratories Advanced Telecommunications Research Institute Int
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MATSUI Tomoko
Spoken Language Translation Research Laboratories, Advanced Telecommunications Research Institute In
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Nakamura Satoshi
Spoken Language Communication Group Knowledge Creating Communication Research Center National Institute Of Information And Communications Technology
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Nakamura Satoshi
Spoken Language Translation Research Laboratories Advanced Telecommunications Research Institute International
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