Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
313 views
in Technique[技术] by (71.8m points)

python - Plot spectogram from mp3

I am trying to plot a spectogram straight from an mp3 file in python 2.7.3 (using ubuntu). I can do it from a wav file as follows.

#!/usr/bin/python
from scikits.audiolab import wavread
from pylab import *

signal, fs, enc = wavread('XC124158.wav')
specgram(signal)
show()

What's the cleanest way to do the same thing from an mp3 file instead of a wav? I don't want to convert all the mp3 files to wav if I can avoid it.

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)

I'd install the Debian/Ubuntu package libav-tools and call avconv to decode the mp3 to a temporary wav file:


Edit: Your other question was closed, so I'll expand my answer here a bit with a simple bandpass filtering example. In the file you linked it looks like most of the birdsong is concentrated in 4 kHz - 5.5 kHz.

import os
from subprocess import check_call
from tempfile import mktemp
from scikits.audiolab import wavread, play
from scipy.signal import remez, lfilter
from pylab import *

# convert mp3, read wav
mp3filename = 'XC124158.mp3'
wname = mktemp('.wav')
check_call(['avconv', '-i', mp3filename, wname])
sig, fs, enc = wavread(wname)
os.unlink(wname)

# bandpass filter
bands = array([0,3500,4000,5500,6000,fs/2.0]) / fs
desired = [0, 1, 0]
b = remez(513, bands, desired)
sig_filt = lfilter(b, 1, sig)
sig_filt /=  1.05 * max(abs(sig_filt)) # normalize

subplot(211)
specgram(sig, Fs=fs, NFFT=1024, noverlap=0)
axis('tight'); axis(ymax=8000)
title('Original')
subplot(212)
specgram(sig_filt, Fs=fs, NFFT=1024, noverlap=0)
axis('tight'); axis(ymax=8000)
title('Filtered')
show()

play(sig_filt, fs)

Bird Song Spectrgrams


与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

...