FrankZxShen's picture
init
ce252ec
raw
history blame
3.17 kB
from modules.F0Predictor.F0Predictor import F0Predictor
import parselmouth
import numpy as np
class PMF0Predictor(F0Predictor):
def __init__(self,hop_length=512,f0_min=50,f0_max=1100,sampling_rate=44100):
self.hop_length = hop_length
self.f0_min = f0_min
self.f0_max = f0_max
self.sampling_rate = sampling_rate
def interpolate_f0(self,f0):
'''
对F0进行插值处理
'''
data = np.reshape(f0, (f0.size, 1))
vuv_vector = np.zeros((data.size, 1), dtype=np.float32)
vuv_vector[data > 0.0] = 1.0
vuv_vector[data <= 0.0] = 0.0
ip_data = data
frame_number = data.size
last_value = 0.0
for i in range(frame_number):
if data[i] <= 0.0:
j = i + 1
for j in range(i + 1, frame_number):
if data[j] > 0.0:
break
if j < frame_number - 1:
if last_value > 0.0:
step = (data[j] - data[i - 1]) / float(j - i)
for k in range(i, j):
ip_data[k] = data[i - 1] + step * (k - i + 1)
else:
for k in range(i, j):
ip_data[k] = data[j]
else:
for k in range(i, frame_number):
ip_data[k] = last_value
else:
ip_data[i] = data[i] #这里可能存在一个没有必要的拷贝
last_value = data[i]
return ip_data[:,0], vuv_vector[:,0]
def compute_f0(self,wav,p_len=None):
x = wav
if p_len is None:
p_len = x.shape[0]//self.hop_length
else:
assert abs(p_len-x.shape[0]//self.hop_length) < 4, "pad length error"
time_step = self.hop_length / self.sampling_rate * 1000
f0 = parselmouth.Sound(x, self.sampling_rate).to_pitch_ac(
time_step=time_step / 1000, voicing_threshold=0.6,
pitch_floor=self.f0_min, pitch_ceiling=self.f0_max).selected_array['frequency']
pad_size=(p_len - len(f0) + 1) // 2
if(pad_size>0 or p_len - len(f0) - pad_size>0):
f0 = np.pad(f0,[[pad_size,p_len - len(f0) - pad_size]], mode='constant')
f0,uv = self.interpolate_f0(f0)
return f0
def compute_f0_uv(self,wav,p_len=None):
x = wav
if p_len is None:
p_len = x.shape[0]//self.hop_length
else:
assert abs(p_len-x.shape[0]//self.hop_length) < 4, "pad length error"
time_step = self.hop_length / self.sampling_rate * 1000
f0 = parselmouth.Sound(x, self.sampling_rate).to_pitch_ac(
time_step=time_step / 1000, voicing_threshold=0.6,
pitch_floor=self.f0_min, pitch_ceiling=self.f0_max).selected_array['frequency']
pad_size=(p_len - len(f0) + 1) // 2
if(pad_size>0 or p_len - len(f0) - pad_size>0):
f0 = np.pad(f0,[[pad_size,p_len - len(f0) - pad_size]], mode='constant')
f0,uv = self.interpolate_f0(f0)
return f0,uv