[speech,fs] = audioread([pathname, filename]); [voice,fs]=extractvoice_simple(speech,-30, -20,0.2); voicex=voice(1:N*16000); [ mfccs, FBEs, frames ] = ... mfcc( voicex, fs, Tw, Ts, alpha, hamming, R, M, C, L ); ceps_mfccx=mfccs(:); [cep,ER]=lpces(voicex,17,...
Multitapering and a wavelet variant of MFCC in speech recognition. IEE Proc. Vision, Image and Signal Proc., 152(1):29-35, Feb 2005.L. P. Ricotti, "Multitapering and a wavelet variant of MFCC in speech recognition," IEE Proc.-Vis. Image Sig- nal Processing, vol. 152, no. 1, pp...
Speaker identification is important research area of speech processing. SI means identifying the speaker based on his spoken speech. The main use of SI is to recognize the speech owner based on the speaking style of the speaker. SI is mainly used in forensic analysis, home control system, ...
Speech recognition has wide range of applications in security systems, healthcare, telephony military, and equipment designed for handicapped. Speech is continuous varying signal. So, proper digital processing algorithm has to be selected for automatic speech recognition system. To obtain required informat...
Davis S, Mermelstein P. Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences[J]. IEEE transactions on acoustics, speech, and signal processing, 1980, 28(4): 357-366 版权声明 本博客的文章除特别说明外均为原创,本人版权所有。欢迎转载,转载请注明作者...
参考 Speech Processing for Machine Learning: Filter banks, Mel-Frequency Cepstral Coefficients (MFCCs) and What's In-Between ASR中常用的语音特征之FBank和MFCC(原理 + Python实现) 英国爱丁堡大学ASR课程讲义 一个成熟的python提取这些特征的包
Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification....
Compute the mel frequency cepstral coefficients of a speech signal using the mfcc function. The function returns delta, the change in coefficients, and deltaDelta, the change in delta values. The log energy value that the function computes can prepend the coefficients vector or replace the first ...
Speech Processing for Machine Learning: Filter banks, Mel-Frequency Cepstral Coefficients (MFCCs) and What's In-Between (2016.4) MFCC特征提取(知乎)-demo操作 机器学习第一步是特征提取,语音领域也不例外。目前使用最多的莫过于Filter banks和MFCC,两者整体相似,MFCC多了一步DCT(离散余弦变换)。
In this work, Mel frequency cepstral coefficients (MFCC) features are extracted for each speech of both training and test samples. In the next step Gaussian mixture model (GMM) is used for classification of the speech based on accent. The overall efficiency of the proposed system to recognize ...