如何用python画出语谱图（spectrogram）和mel谱图（mel spectrogram）

如何用python画出语谱图（spectrogram）和mel谱图（mel spectrogram）

1.准备环境
①python
②libsora
③matplotlib

Notes：pip install 直接一步到位

2.具体代码
①语谱图（spectrogram）

import librosa
import numpy as np
import matplotlib.pyplot as plt

path = \"./test.wav\"

# sr=None声音保持原采样频率， mono=False声音保持原通道数
data, fs = librosa.load(path, sr=None, mono=False) 
 
L = len(data)
print(\'Time:\', L / fs)

#归一化
data = data * 1.0 / max(data)

#0.025s
framelength = 0.025
#NFFT点数=0.025*fs
framesize = int(framelength * fs)
print(\"NFFT:\", framesize)

#画语谱图
plt.specgram(data, NFFT=framesize, Fs=fs, window=np.hanning(M=framesize))
plt.ylabel(\'Frequency\')
plt.xlabel(\'Time(s)\')
plt.title(\'Spectrogram\')
plt.show()

②mel谱图

import librosa.display
import numpy as np
import matplotlib.pyplot as plt

path = \"./test.wav\"

# sr=None声音保持原采样频率， mono=False声音保持原通道数
data, fs = librosa.load(path, sr=None, mono=False)

L = len(data)
print(\'Time:\', L / fs)

# 归一化
data = data * 1.0 / max(data)

# 0.025s
framelength = 0.025
# NFFT点数=0.025*fs
framesize = int(framelength * fs)
print(\"NFFT:\", framesize)

#提取mel特征
mel_spect = librosa.feature.melspectrogram(data, sr=fs, n_fft=framesize)
#转化为log形式
mel_spect = librosa.power_to_db(mel_spect, ref=np.max)

#画mel谱图
librosa.display.specshow(mel_spect, sr=fs, x_axis=\'time\', y_axis=\'mel\')
plt.ylabel(\'Mel Frequency\')
plt.xlabel(\'Time(s)\')
plt.title(\'Mel Spectrogram\')
plt.show()