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- LPCC cepstrum 线性预测倒谱系数
- At last, the special ASR algorithm (LPCC, derivative cepstrum method, improved DTW and Pitch) is realized. 最后介绍了本系统所采用的语音识别算法(LPCC、一阶导倒谱距失真测度、放宽端的DTW和基音周期)的设计思想并给出仿真结果和试验数据。
- The performances of the system are compared and analyzed when the feature extraction is based on Linear Prediction Cepstrum Coefficient(LPCC) or Mel Frequency Ceps. 给出了系统整体的软硬件框架,并比较和分析了分别将线性预测倒谱参数和美尔频标倒谱参数作为语音特征参数时系统的性能,为语音识别的嵌入式应用提供了参考依据。
- The cepstrum of the slice named dimension cepstrum. 文章详细地描述了积分双谱的计算量和估计误差,其相对于双谱来说,计算量和估计误差是显著地减小了。
- Linear Prediction Cepstrum Coefficient(LPCC) 线性预测倒谱系数
- Industry using shows the life of abrasion resistance blade of LPCC is over five years.Figs 3,tables 2 and refs 5. 工程应用的结果表明,百叶窗浓缩器抗磨叶片使用寿命可以达到5年以上。
- Durbin algorithm of LPC, the use of this parameter can not be calculated into one LPCC. 杜宾算法计算的LPC,利用此参数可进一不计算出LPCC。
- And an effective reference for cost control of future LPCC projects is thus provided. 为以后的石油化工项目成本控制提供有益的参考。
- The new speech parameter called ACW cepstrum is introduced,which proves to be more robust in the telephone channel. 根据信道对参数的影响提出一种ACW倒谱参数 ,实验证明了其对信道影响具有较稳健的特性
- An improved speech pitch detection algorithm based on modified cepstrum model is proposed. 摘要该文提出了一种基于修正倒谱模型的改进的倒谱基音检测算法。
- The pitch period of the voiced speech is extracted from the cepstrum of predictive residual. 最后根据倒谱的特征求得浊音语音的基音周期。
- The weighted LPCC feature based on the distortion of speech coding was explored to reduce the influence under the matched condition. 在前者中,通过分析语音编码对LPCC参数的影响,提出了一种基于编码失真的LPCC加权参数。
- Cepstrum analysis of voice and image processing are widely used in nonlinear signal processing technology. 倒频谱分析是语音和图象处理中广泛应用的非线性信号处理技术。
- Cepstrum analysis is divided into two categories of real and complex cepstrum cepstrum. 倒频谱分析法分为实倒频谱和复倒频谱两类。
- The digital signature can be extracted from the embedded voice signal by the method of cepstrum analyzing. 通过倒谱分析,能够完整地从隐写语音信号中提取出数字签名。
- The experimental results show that order cepstrum analysis can effectively diagnosis the gear faults. 实验分析结果表明该方法能有效地识别齿轮的故障类型。
- The comparative analysis of the experimental data is explained: the accuracy of HF parameter drawing base on Non-linear theoretical foundation greater than LPCC. 实验数据比较分析说明:基于非线性理论基础上的HF特征提取方法的精确性大于传统的基于线性理论基础上的传统LPC复倒谱说话人识别特征提取方法。
- This paper presents a blind audio watermarking algorithm based on cepstrum transform. 摘要 提出了一种基于复倒谱变换的数字音频水印算法。
- In this paper, we use full pole model to obtain speech signal LPC, then deduce it"s LPCC, and we use the LPCC difference to describe speaker"s track dynamic movement. 本文应用全极点模型,提取语音信号的线性预测系数,并推导出其倒谱系数,获得线性预测倒谱差分,用以描述说话人声道的动态变化。
- Combining the cepstrum method could identify the characteristic frequency availably. 结合倒频谱方法可以有效地识别故障特征频率。