Fukuda T | Tokyo Research Laboratory Ibm Japan Ltd.
スポンサーリンク
概要
関連著者
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NITTA Tsuneo
Graduate School of Engineering, Toyohashi University of Technology
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Nitta T
Graduate School Of Engineering Toyohashi University Of Technology
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Nitta Tsuneo
The Graduate School Of Engineering Toyohashi University Of Technology
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GHULAM Muhammad
Graduate School of Engineering, Toyohashi University of Technology
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FUKUDA Takashi
Tokyo Research Laboratory, IBM Japan Ltd.
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Fukuda T
Tokyo Research Laboratory Ibm Japan Ltd.
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Ghulam Muhammad
Graduate School Of Engineering Toyohashi University Of Technology
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Nitta Tsuneo
Graduate School Of Engineering Toyohashi University Of Technology
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KATSURADA Kouichi
Graduate School of Engineering, Toyohashi University of Technology
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Katsurada Kouichi
Graduate School Of Engineering Toyohashi University Of Technology
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Nurul Huda
Graduate School Of Engineering Toyohashi University Of Technology
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Horikawa Junsei
The Graduate School Of Engineering Toyohashi University Of Technology
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GHULAM Muhammad
the Graduate School of Engineering, Toyohashi University of Technology
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FUKUDA Takashi
the Graduate School of Engineering, Toyohashi University of Technology
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KATSURADA Kouichi
the Graduate School of Engineering, Toyohashi University of Technology
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SATO Takaharu
Graduate School of Engineering, Toyohashi University of Technology
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FUKUDA Takashi
Graduate School of Engineering, Toyohashi University of Technology
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Sato T
Graduate School Of Engineering Toyohashi University Of Technology:(present Address)fujitsu Tohoku Sy
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Fukuda Takashi
Tokyo Research Laboratory Ibm Japan Ltd.
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Fukuda Takashi
Graduate School Of Engineering Toyohashi University Of Technology
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FUKUDA TAKASHI
The Government Industrial Development Laboratory
著作論文
- Canonicalization of Feature Parameters for Robust Speech Recognition Based on Distinctive Phonetic Feature (DPF) Vectors
- PS-ZCPA Based Feature Extraction with Auditory Masking, Modulation Enhancement and Noise Reduction for Robust ASR(Speech Recognition, Statistical Modeling for Speech Processing)
- Confidence Scoring for Accurate HMM-Based Speech Recognition by Using Monophone-Level Normalization Based on Subspace Method (Special Issue on Speech Information Processing)