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