PS-ZCPA Based Feature Extraction with Auditory Masking, Modulation Enhancement and Noise Reduction for Robust ASR(Speech Recognition, <Special Section> Statistical Modeling for Speech Processing)
スポンサーリンク
概要
- 論文の詳細を見る
A pitch-synchronous (PS) auditory feature extraction method based on ZCPA (Zero-Crossings Peak-Amplitudes) was proposed previously and showed more robustness over a conventional ZCPA and MFCC based features. In this paper, firstly, a non-linear adaptive threshold adjustment procedure is introduced into the PS-ZCPA method to get optimal results in noisy conditions with different signal-to-noise ratio (SNR). Next, auditory masking, a well-known auditory perception, and modulation enhancement that simulates a strong relationship between modulation spectrums and intelligibility of speech are embedded into the PS-ZCPA method. Finally, a Wiener filter based noise reduction procedure is integrated into the method to make it more noise-robust, and the performance is evaluated against ETSI ES202 (WI008), which is a standard front-end for distributed speech recognition. All the experiments were carried out on Aurora-2J database. The experimental results demonstrated improved performance of the PS-ZCPA method by embedding auditory masking into it, and a slightly improved performance by using modulation enhancement. The PS-ZCPA method with Wiener filter based noise reduction also showed better performance than ETSI ES202 (WI008).
- 社団法人電子情報通信学会の論文
- 2006-03-01
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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KATSURADA Kouichi
Graduate School of Engineering, Toyohashi University of Technology
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Fukuda T
Tokyo Research Laboratory Ibm Japan Ltd.
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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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Ghulam Muhammad
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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FUKUDA TAKASHI
The Government Industrial Development Laboratory
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