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- The algorithm adopts Mel frequency cepstrum coefficients (MFCC), which has lower space complexity than Bark spectrum, as feature representations for speech samples. 该算法采用12阶美尔倒谱参数(MFCC)作为语音信号特征向量，其空间复杂度小于巴克谱。
- In present,the most basical used parameters for speaker identification are linear predictive coding(LPC) parameter,Mel frequency cepstrum coefficient(MFCC),etc. 目前在说话人识别中常用的特征是线性预测编码(LPC)参数和美尔倒谱系数(MFCC)等。
- MFCC (Mel frequency cepstrum coefficient) 美尔频率倒谱系数
- Mel Frequency Cepstrum Coefficient ( MFCC) 梅尔刻度式倒谱参数（MFCC）
- Mel Frequency Cepstrum Coefficient (MFCC) 美尔倒谱系数
- Mel Frequency Cepstrum Coefficient(MFCC) Mel倒谱系数（MFCC）
- Mel frequency cepstrum coefficient Mel倒谱系数
- Mel frequency cepstrum coefficients Mel倒谱系数
- Mel frequency cepstrum coeficient 美尔频率倒谱系数
- Keywords Speaker identification Complexity Mel frequency cepstrum coefficient（MFCC）; 说话人识别;复杂性;美尔倒谱系数;
- Improved Approaches of Processing Perceptual Linear Prediction（PLP）and Mel Frequency Cepstrum Coefficient（MFCC）Parameters for Robust Speech Recognition 题名:强健性语音辨识;中处理;感知线性预测参;数;与梅尔倒频谱系数;之进一步方法
- Mel frequency cepstrum 美尔频率倒谱
- 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。
- mel - frequency cepstrum coefficient ( MFCC ) mel频标倒频系数（MFCC）
- The spectral envelope is the mel frequency scale and IDFT is used to extract the estimate of sample autocorrelations. 再由语音信号谱包估计抽样自相关 ,用 IDFT提取抽样自相关估计。
- During the experiment,MFCC(Mel Frequency Ceptral Coefficient) is adopted to speaker speech feature parameters. 实验中,采用美尔倒谱系数(MFCC)作为话者语音特征参数。
- Mel Frequency Cepstral Coefficients 美尔频率倒谱系数（MFCC）
- Mel Frequency Cepstral Coefficients(MFCC) 梅尔倒谱系数（MFCC）
- Mel frequency cepstral coefficient 美尔倒谱系数
