mfcc

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。

Selected for use MFCC and the difference and divided the characteristic parameter as phonetic recognition , to describe the non-linear characteristic of frequency of sense of hearing of ears of people .

选用美尔倒谱系数及其差分作为语音识别的特征参数，来描述人耳的听觉频率非线性特性。

An improved feature extraction algorithm based on MFCC was proposed .

提出了一种基于MFCC特征提取的改进算法。

Study on speech quality evaluation based on improved MFCC

基于改进MFCC语音特征参数的语音质量评估的研究

The Research of Robust Speech Recognition in Noise Environment Based on MFCC

噪声环境下基于MFCC的鲁棒语音识别研究

Study on feature parameter extraction for MFCC based on System Vue

基于SystemVue的MFCC特征参数提取研究

An Algorithm for MFCC Based on Speech Spectrum Harmonic Samples Extraction

基于语音频谱包络抽取的MFCC算法

Research on a Speaker Recognition System using MFCC Features and Vector Quantization

基于MFCC和VQ码书的说话人识别系统研究

The influence of fundamental frequency to performance of speaker recognition using MFCC

MFCC中的基音频率信息对说话人识别系统性能的影响

Improved MFCC Feature Extraction Algorithm Based on Hearing Masking Effect

基于听觉掩蔽效应的改进MFCC特征提取算法

Speaker Recognition Model Based on MFCC and Combined Features

基于MFCC等组合特征的说话人识别模型

Speech Recognition Speed up Research Based on MFCC

基于MFCC的语音识别加速技术研究

The Recognition Performance and Robustness of High Order MFCC for Speaker Recognition

高阶MFCC的话者识别性能及其噪声鲁棒性

An Efficient Speaker Feature Extraction Method Based on MFCC

基于MFCC参数的说话人特征提取算法的改进

Improved speech recognition algorithm based on MFCC feature

改进的混合MFCC语音识别算法研究

A audio recognition arithmetic based on MFCC is proposed .

研究了单一音频信号的识别方法。

A Fast Algorithm for Extracting Speech Feature Parameter MFCC on Microcontroller

一种在单片机上提取语音特征参数MFCC的快速算法

Recognition of speech under G - force based on weighted features of MFCC

MFCC特征加权应力影响下的变异语音识别

MFCC feature extraction of speech based on pitch period

基于基音周期的语音MFCC参数提取

Speech emotion recognition based on improved MFCC with EMD is proposed .

具体研究工作如下：1.提出了一种基于经验模态分解的改进MFCC的情感识别方法。

It proposes a method which combines MFCC based system and Pitch based system to gain better result .

本文提出了一个基于基音的辅助系统与MFCC主系统结合的方法。

MFCC is the main parameter for speech recognition .

MFCC是语音识别的重要参数。

Using mixed window function and subband spectrum centroid in MFCC feature extraction process

混合窗函数和子带频谱质心在MFCC特征提取过程中的应用

The extraction and application of phonetic characteristic parameter MFCC

语音特征参数MFCC的提取及其应用

In order to improve the dynamic performance , we added the first difference to the standard MFCC .

为了改善参数动态性能，对MFCC进行二次特征处理，追加了标准MFCC的一阶差分。

LPC and MFCC are two most popular features used in speaker identification .

线性预测系数（LPC）与mel倒谱系数（MFCC）作为说话人识别的两种常用特征，取得了较高的识别率。

According to the character of MFCC algorithm , get fast fitted MFCC algorithm .

根据MFCC算法的特点，得到快速定点化处理的MFCC算法。

A Fast Fixed-Point Scheme for MFCC in a DSP Speech Controller

DSP语音控制器中MFCC参数的定点快速算法

Speech emotion recognition based on the fusion of sample entropy and MFCC is proposed .

提出了一种基于样本熵和MFCC融合的语音情感识别方法。

Vehicle Classification by Acoustic Signal with Modified MFCC

基于声信号的改进MFCC特征的地面车辆分类