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activlev.rar
- calculates the active level of a speech segment according to ITU-T recommendation P.56.,calculates the active level of a speech segment according to ITU-T recommendation P.56.
Peter_Howell_Stevie_Sackin_and_Kazan_Glenn
- Peter Howell, Stevie Sackin, and Kazan Glenn Development of a Two-Stage Procedure for the Automatic Recognition of Dysfluencies in the Speech of Children Who Stutter: II. ANN Recognition of Repetitions and Prolongations With Supplied Word Segment M
PLAY
- 把语音芯片ISD1420录放音时间20秒分成20段，每段一秒，调用录音子程序，录入语音，建立语音库，语音录入结束后，根据段地址，调用放音子程序，还原原来录入语音信号。- The voice chip ISD1420 sound recording time of 20 seconds is divided into 20 segments, each second, a subroutine call recording, voice input, speech database estab
fenge
- 用于提取一段语音中单独的每个字词，matlab下编写，经检测很好用。注意不是检测一段语音中的一个字词，而是所有的。-to detect every word in a speech segment. made in matlab. mind you , it s meant to detect every word, not only the first word
Kalmanflt
- filter for denoising noisy speech (corrupted by white noise). Kalman filtering of noisy speech usually have two steps: Estimating the AR parameters of speech segment
tibaoluo
- 基于倒谱短时部分反映了语音的声道特性，先用汉明窗取一帧语音，然后经变换得到语音倒谱，将倒谱短时部分取出，进行正交反变换后将得到声道的对数谱，即得到语音频谱的包络。将频谱包络和频谱画在一张图上，有很好的对比效果。获取的包络效果十分好。-Based Cepstral partly reflects the short channel characteristics of the speech, first take a Hamming window with a frame of speech, a
SegSNR_esitmate
- 分段信噪比测试，主要是用于语音增强，语音编码后的测试使用-segment SNR test, primarily for speech enhancement, speech coding after testing
Speech Encoding - Frequency Analysis MATLAB
- The speech signal for the particular isolated word can be viewed as the one generated using the sequential generating probabilistic model known as hidden Markov model (HMM). Consider there are n states in the HMM. The particular isolated speech sig
107551700第三次作业
- 根据短时傅里叶变换原理，计算并显示该语音段的短时幅度谱和功率谱；根据语谱图显示原理，编程实现该语音段语谱图的计算和显示，并尽量多地分析出语谱图包含的语音特征信息,用MATLAB提供的倒谱计算函数，显示该语音段的复倒谱和倒谱(According to the principle of short-term Fourier transform, the short range spectrum and power spectrum of the speech segment are calculat
ABSE
- 熵值越大则每个符号包含的平均信息量越大。有研究发现，在有噪声的语音信号中，语音信号的熵和噪声信号的熵存在着较大的差异，对噪声信号来说在整个频带内分布相对平坦，熵值小，语音信号集中在某些特定频段内，熵值大。因此利用这个差异可以区分噪音段和语音段。(The greater the entropy is, the greater the average information of each symbol is. It is found that, in noisy speech signals, t
audio_tezheng
- 语音信号的时域、频域与倒谱域分析。 1.分析一帧清音和浊音的自相关函数和倒谱系数 2.用Matlab画出该段语音的时域波形、短时能量、短时平均幅度、短时过零率、短时过电平率 3.选择一帧无声、清音和浊音的语音，用Matlab画出它们的对数幅度谱(Time domain, frequency domain and cepstrum domain analysis of speech signals. 1. Analyze the autocorrelation function and c