Update HarvestF0Predictor.py
This commit is contained in:
parent
a54b041228
commit
f540622ed2
|
@ -1,7 +1,6 @@
|
|||
from modules.F0Predictor.F0Predictor import F0Predictor
|
||||
import pyworld
|
||||
import numpy as np
|
||||
import scipy
|
||||
|
||||
class HarvestF0Predictor(F0Predictor):
|
||||
def __init__(self,hop_length=512,f0_min=50,f0_max=1100,sampling_rate=44100):
|
||||
|
@ -10,6 +9,44 @@ class HarvestF0Predictor(F0Predictor):
|
|||
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 resize_f0(self,x, target_len):
|
||||
source = np.array(x)
|
||||
source[source<0.001] = np.nan
|
||||
|
@ -17,17 +54,6 @@ class HarvestF0Predictor(F0Predictor):
|
|||
res = np.nan_to_num(target)
|
||||
return res
|
||||
|
||||
def resize_f0_uv(self,x, target_len):
|
||||
source = np.array(x)
|
||||
vuv_vector = np.zeros_like(x)
|
||||
vuv_vector[x > 0.0] = 1.0
|
||||
vuv_vector[x < 0.001] = 0.0
|
||||
source[source<0.001] = np.nan
|
||||
target = np.interp(np.arange(0, len(source)*target_len, len(source))/ target_len, np.arange(0, len(source)), source)
|
||||
res = np.nan_to_num(target)
|
||||
vuv_vector = np.ceil(scipy.ndimage.zoom(vuv_vector,target_len/len(vuv_vector),order = 0))
|
||||
return res,vuv_vector
|
||||
|
||||
def compute_f0(self,wav,p_len=None):
|
||||
if p_len is None:
|
||||
p_len = wav.shape[0]//self.hop_length
|
||||
|
@ -39,7 +65,7 @@ class HarvestF0Predictor(F0Predictor):
|
|||
frame_period=1000 * self.hop_length / self.sampling_rate,
|
||||
)
|
||||
f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.fs)
|
||||
return self.resize_f0(f0, p_len)
|
||||
return self.interpolate_f0(self.resize_f0(f0, p_len))[0]
|
||||
|
||||
def compute_f0_uv(self,wav,p_len=None):
|
||||
if p_len is None:
|
||||
|
@ -52,4 +78,4 @@ class HarvestF0Predictor(F0Predictor):
|
|||
frame_period=1000 * self.hop_length / self.sampling_rate,
|
||||
)
|
||||
f0 = pyworld.stonemask(wav.astype(np.double), f0, t, self.sampling_rate)
|
||||
return self.resize_f0_uv(f0, p_len)
|
||||
return self.interpolate_f0(self.resize_f0(f0, p_len))
|
||||
|
|
Loading…
Reference in New Issue