from lib.infer_pack.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