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Automatic Speech Recognition Based on Cepstral Coefficients and a Melbased Discrete Energy Operator

机译：基于倒谱系数和基于mel的离散能量算子的自动语音识别

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Hesham Tolba;
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年度 1998
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1. Enhanced Automatic Speech Recognition System Based on Enhancing Power-Normalized Cepstral Coefficients [J] . Mohamed Tamazin, Ahmed Gouda, Mohamed Khedr Applied Sciences . 2019,第10期

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2. Exploiting independent filter bandwidth of human factor cepstral coefficients in automatic speech recognition [J] . Skowronski MD, Harris JG The Journal of the Acoustical Society of America . 2004,第3期

机译：在语音自动识别中利用人为因素倒谱系数的独立滤波器带宽
3. Automatic Voice Pathology Detection With Running Speech by Using Estimation of Auditory Spectrum and Cepstral Coefficients Based on the All-Pole Model [J] . Ali Zulfiqar, Elamvazuthi Irraivan, Alsulaiman Mansour, Journal of voice: official journal of the Voice Foundation . 2016,第6期

机译：基于全极点模型的听觉频谱和倒谱系数估计的运行语音自动语音病理检测
4. Automatic speech recognition based on cepstral coefficients and a mel-based discrete energy operator [C] . Tolba, H., OShaughnessy, . 1998

机译：基于倒谱系数和基于mel的离散能量算子的自动语音识别
5. Estimation of cepstral coefficients for robust speech recognition. [D] . Indrebo, Kevin M. 2008

机译：倒频谱系数的估计，用于鲁棒的语音识别。
6. The application of fractional Mel cepstral coefficient in deceptive speech detection [O] . Xinyu Pan, Heming Zhao, Yan Zhou -1

机译：分数梅尔倒谱系数在欺骗性语音检测中的应用
7. Automatic speaker recognition dynamic feature identification and classification using distributed discrete cosine transform based mel frequency cepstral coefficients and fuzzy vector quantization [O] . Hossan M 2011

机译：基于分布式离散余弦变换的梅尔频率倒谱系数和模糊矢量量化自动说话人识别动态特征识别与分类

Automatic Speech Recognition Based on Cepstral Coefficients and a Melbased Discrete Energy Operator

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