Извлечение аудио функций
Считывайте аудиосигнал.
[audioIn,fs] = audioread("Counting-16-44p1-mono-15secs.wav");Создайте audioFeatureExtractor для извлечения центроида спектра Корки, куртоза спектра Корки и pitch аудиосигнала.
aFE = audioFeatureExtractor("SampleRate",fs, ... "SpectralDescriptorInput","barkSpectrum", ... "spectralCentroid",true, ... "spectralKurtosis",true, ... "pitch",true)
aFE =
audioFeatureExtractor with properties:
Properties
Window: [1024x1 double]
OverlapLength: 512
SampleRate: 44100
FFTLength: []
SpectralDescriptorInput: 'barkSpectrum'
Enabled Features
spectralCentroid, spectralKurtosis, pitch
Disabled Features
linearSpectrum, melSpectrum, barkSpectrum, erbSpectrum, mfcc, mfccDelta
mfccDeltaDelta, gtcc, gtccDelta, gtccDeltaDelta, spectralCrest, spectralDecrease
spectralEntropy, spectralFlatness, spectralFlux, spectralRolloffPoint, spectralSkewness, spectralSlope
spectralSpread, harmonicRatio
To extract a feature, set the corresponding property to true.
For example, obj.mfcc = true, adds mfcc to the list of enabled features.
Функции extract для извлечения функций из аудиосигнала. Нормализуйте функции по их среднему и стандартному отклонению.
features = extract(aFE,audioIn); features = (features - mean(features,1))./std(features,[],1);
Постройте график нормализованных функций с течением времени.
idx = info(aFE); duration = size(audioIn,1)/fs; subplot(2,1,1) t = linspace(0,duration,size(audioIn,1)); plot(t,audioIn) subplot(2,1,2) t = linspace(0,duration,size(features,1)); plot(t,features(:,idx.spectralCentroid), ... t,features(:,idx.spectralKurtosis), ... t,features(:,idx.pitch)); legend("Spectral Centroid","Spectral Kurtosis", "Pitch") xlabel("Time (s)")
