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python - 为什么 MFCC 提取库返回不同的值?

转载 作者:太空狗 更新时间:2023-10-30 01:25:05 26 4
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我正在使用两个不同的库提取 MFCC 特征:

  • python_speech_features 库
  • BOB 库

但是两者的输出是不同的,甚至形状也不一样。那是正常的吗?还是我缺少一个参数?

我的代码的相关部分如下:

import bob.ap
import numpy as np
from scipy.io.wavfile import read
from sklearn import preprocessing
from python_speech_features import mfcc, delta, logfbank

def bob_extract_features(audio, rate):
#get MFCC
rate = 8000 # rate
win_length_ms = 30 # The window length of the cepstral analysis in milliseconds
win_shift_ms = 10 # The window shift of the cepstral analysis in milliseconds
n_filters = 26 # The number of filter bands
n_ceps = 13 # The number of cepstral coefficients
f_min = 0. # The minimal frequency of the filter bank
f_max = 4000. # The maximal frequency of the filter bank
delta_win = 2 # The integer delta value used for computing the first and second order derivatives
pre_emphasis_coef = 0.97 # The coefficient used for the pre-emphasis
dct_norm = True # A factor by which the cepstral coefficients are multiplied
mel_scale = True # Tell whether cepstral features are extracted on a linear (LFCC) or Mel (MFCC) scale

c = bob.ap.Ceps(rate, win_length_ms, win_shift_ms, n_filters, n_ceps, f_min,
f_max, delta_win, pre_emphasis_coef, mel_scale, dct_norm)
c.with_delta = False
c.with_delta_delta = False
c.with_energy = False

signal = np.cast['float'](audio) # vector should be in **float**
example_mfcc = c(signal) # mfcc + mfcc' + mfcc''
return example_mfcc


def psf_extract_features(audio, rate):
signal = np.cast['float'](audio) #vector should be in **float**
mfcc_feature = mfcc(signal, rate, winlen = 0.03, winstep = 0.01, numcep = 13,
nfilt = 26, nfft = 512,appendEnergy = False)

#mfcc_feature = preprocessing.scale(mfcc_feature)
deltas = delta(mfcc_feature, 2)
fbank_feat = logfbank(audio, rate)
combined = np.hstack((mfcc_feature, deltas))
return mfcc_feature



track = 'test-sample.wav'
rate, audio = read(track)

features1 = psf_extract_features(audio, rate)
features2 = bob_extract_features(audio, rate)

print("--------------------------------------------")
t = (features1 == features2)
print(t)

最佳答案

However the output of the two is different and even the shapes are not the same. Is that normal?

是的,有不同的算法,每个实现选择自己的风格

or is there a parameter that I am missing?

这不仅与参数有关,还存在算法差异,例如窗口形状(汉明与汉宁)、梅尔过滤器的形状、梅尔过滤器的启动、梅尔过滤器的归一化、提升、dct flavor 等等。

如果你想要相同的结果只使用单个库进行提取,同步它们是非常无望的。

关于python - 为什么 MFCC 提取库返回不同的值?,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/52112204/

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