MFCC:梅尔频率倒谱系数
梅尔频率倒谱系数(Mel Frequency Cepstral Coefficients,简称MFCC)是一种广泛应用于语音信号处理和音频特征提取的技术。它通过模拟人耳对声音频率的感知特性,将音频信号转换为一组具有代表性的系数,便于后续的分析与识别。由于名称较长,在学术论文和技术文档中常缩写为MFCC,以简化书写并提高交流效率。这一术语在声学、人工智能及语音识别等多个综合领域中十分常见。
Mel frequency cepstral coefficients具体释义
Mel frequency cepstral coefficients的英文发音
例句
- Based on analyzing the traditional Mel frequency cepstral coefficients(MFCC) extraction, wavelet packet and weighted filter, a new method of feature extraction is proposed.
- 本文在分析传统Mel频标倒谱系数提取过程的基础上,结合小波包分析和滤波器加权分析,提出了一种新的特征参数提取方法。
- We research and implement the process of the Mel Frequency Cepstral Coefficients ( MFCC ), for the MFCC using the principle of hearing and the decorrelation properties of cepstral. ( 3 ) Speaker recognition module is kernel of the whole system.
- 我们研究了利用了听觉原理和倒谱的解相关特性的Mel倒谱参数,实现了Mel倒谱参数的提取过程;(3)在系统实现上,说话人识别是系统的核心模块。
- Based on fix-point and principal component analysis technology, the realization of real-time text-independent speaker recognition system, which takes Mel frequency cepstral coefficients(MFCC) as the feature parameter, is presented.
- 以Mel倒谱系数为说话人特征,运用主成分分类技术,结合定点数计算技术实现实时说话人自动识别。
- Most existing studies in music retrieve via low-level features such as Mel frequency cepstral coefficient ( MFCC ) or other spectral coefficients.
- 而现有的大多数情况是通过分析梅尔频谱系数等特征(或其它的光谱系数这些低层(low-levelfeatures))对音乐进行检索。
- DFT is applied to extract several basic audio features, including the Mel-frequency cepstral coefficients and pitch frequency which are concatenated to form a high-dimensional vector.
- 在实现音乐分类中,先使用傅里叶变换等方法从每一段音乐中提取音频特征,包括Mel倒谱系数及基音频率等,并将它们按比例组成一个高维向量;
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