def compute_music_power(wav_filename,tf_config,
normalize_factor,
fftLen,stft_step,
min_freq,max_freq,src_num,
music_win_size,music_step):
setting={}
# read wav
print "... reading", wav_filename
wav_data=simmch.read_mch_wave(wav_filename)
wav=wav_data["wav"]/normalize_factor
fs=wav_data["framerate"]
# print info
print "# #channels : ", wav_data["nchannels"]
setting["nchannels"]=wav_data["nchannels"]
print "# sample size : ", wav.shape[1]
setting["nsamples"]=wav.shape[1]
print "# sampling rate : ", fs,"Hz"
setting["framerate"]=fs
print "# duration : ", wav_data["duration"],"sec"
setting["duration"]=wav_data["duration"]
# reading data
df=fs*1.0/fftLen
# cutoff bin
min_freq_bin=int(np.ceil(min_freq/df))
max_freq_bin=int(np.floor(max_freq/df))
print "# min freq. :",min_freq_bin*df , "Hz"
setting["min_freq"]=min_freq_bin*df
print "# max freq. :",max_freq_bin*df , "Hz"
setting["max_freq"]=max_freq_bin*df
print "# freq. step:",df, "Hz"
setting["freq_step"]=df
print "# min freq. bin index:",min_freq_bin
print "# max freq. bin index:",max_freq_bin
# apply STFT
win = hamming(fftLen) # ハミング窓
spec=simmch.stft_mch(wav,win,stft_step)
spec_m=spec[:,:,min_freq_bin:max_freq_bin]
# apply MUSIC method
## power[frame, freq, direction_id]
print "# src_num:",src_num
setting["src_num"]=src_num
setting["step_ms"]=1000.0/fs*stft_step
setting["music_step_ms"]=1000.0/fs*stft_step*music_step
power=compute_music_spec(spec_m,src_num,tf_config,df,min_freq_bin,
win_size=music_win_size,
step=music_step)
p=np.sum(np.real(power),axis=1)
m_power=10*np.log10(p+1.0)
m_full_power=10*np.log10(np.real(power)+1.0)
return spec,m_power,m_full_power,setting
step = 160 #fftLen / 4 df=fs1*1.0/fftLen # cutoff bin min_freq=0 max_freq=10000 min_freq_bin=int(np.ceil(min_freq/df)) max_freq_bin=int(np.floor(max_freq/df)) sidelobe_freq_bin=int(np.floor(2000/df)) print "# min freq:",min_freq print "# max freq:",max_freq print "# min fft bin:",min_freq_bin print "# max fft bin:",max_freq_bin # STFT win = hamming(fftLen) # ハミング窓 spec1=simmch.stft_mch(wav1,win,step) spec2=simmch.stft_mch(wav2,win,step) ## ## nframe1=spec1.shape[1] nframe2=spec2.shape[1] nframe=min(nframe1,nframe2) spec1_temp=spec1[:,0:nframe,min_freq_bin:max_freq_bin] spec2_temp=spec2[:,0:nframe,min_freq_bin:max_freq_bin] if options.noise is not None: w=wiener_filter_eigen(spec1_temp,spec2_temp,win_size=nframe,r_step=1) print "# filter:",w.shape out_spec=apply_filter_eigen(spec1_temp,w) # ISTFT recons=simmch.istft_mch(out_spec, win, step)
step = 160 #fftLen / 4
df = fs1 * 1.0 / fftLen
# cutoff bin
min_freq = 0
max_freq = 10000
min_freq_bin = int(np.ceil(min_freq / df))
max_freq_bin = int(np.floor(max_freq / df))
sidelobe_freq_bin = int(np.floor(2000 / df))
print "# min freq:", min_freq
print "# max freq:", max_freq
print "# min fft bin:", min_freq_bin
print "# max fft bin:", max_freq_bin
# STFT
win = hamming(fftLen) # ハミング窓
spec1 = simmch.stft_mch(wav1, win, step)
spec2 = simmch.stft_mch(wav2, win, step)
##
##
nframe1 = spec1.shape[1]
nframe2 = spec2.shape[1]
nframe = min(nframe1, nframe2)
spec1_temp = spec1[:, 0:nframe, min_freq_bin:max_freq_bin]
spec2_temp = spec2[:, 0:nframe, min_freq_bin:max_freq_bin]
if options.noise is not None:
w = wiener_filter_eigen(spec1_temp,
spec2_temp,
win_size=nframe,
r_step=1)
print "# filter:", w.shape
