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import os
import librosa
import pyworld
import utils
import numpy as np
from scipy.io import wavfile
class FeatureInput(object):
def __init__(self, samplerate=16000, hop_size=160):
self.fs = samplerate
self.hop = hop_size
self.f0_bin = 256
self.f0_max = 1100.0
self.f0_min = 50.0
self.f0_mel_min = 1127 * np.log(1 + self.f0_min / 700)
self.f0_mel_max = 1127 * np.log(1 + self.f0_max / 700)
def compute_f0(self, path):
x, sr = librosa.load(path, sr=self.fs)
assert sr == self.fs
f0, t = pyworld.dio(
x.astype(np.double),
fs=sr,
f0_ceil=800,
frame_period=1000 * self.hop / sr,
)
f0 = pyworld.stonemask(x.astype(np.double), f0, t, self.fs)
for index, pitch in enumerate(f0):
f0[index] = round(pitch, 1)
return f0
# for numpy # code from diffsinger
def coarse_f0(self, f0):
f0_mel = 1127 * np.log(1 + f0 / 700)
f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
self.f0_bin - 2
) / (self.f0_mel_max - self.f0_mel_min) + 1
# use 0 or 1
f0_mel[f0_mel <= 1] = 1
f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
f0_coarse = np.rint(f0_mel).astype(np.int)
assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
f0_coarse.max(),
f0_coarse.min(),
)
return f0_coarse
# for tensor # code from diffsinger
def coarse_f0_ts(self, f0):
f0_mel = 1127 * (1 + f0 / 700).log()
f0_mel[f0_mel > 0] = (f0_mel[f0_mel > 0] - self.f0_mel_min) * (
self.f0_bin - 2
) / (self.f0_mel_max - self.f0_mel_min) + 1
# use 0 or 1
f0_mel[f0_mel <= 1] = 1
f0_mel[f0_mel > self.f0_bin - 1] = self.f0_bin - 1
f0_coarse = (f0_mel + 0.5).long()
assert f0_coarse.max() <= 255 and f0_coarse.min() >= 1, (
f0_coarse.max(),
f0_coarse.min(),
)
return f0_coarse
def save_wav(self, wav, path):
wav *= 32767 / max(0.01, np.max(np.abs(wav))) * 0.6
wavfile.write(path, self.fs, wav.astype(np.int16))
if __name__ == "__main__":
wavPath = "./data/waves"
outPath = "./data/label"
if not os.path.exists("./data/label"):
os.mkdir("./data/label")
# define model and load checkpoint
hps = utils.get_hparams_from_file("./configs/singing_base.json")
featureInput = FeatureInput(hps.data.sampling_rate, hps.data.hop_length)
vits_file = open("./filelists/vc_file.txt", "w", encoding="utf-8")
for spks in os.listdir(wavPath):
if os.path.isdir(f"./{wavPath}/{spks}"):
os.makedirs(f"./{outPath}/{spks}")
for file in os.listdir(f"./{wavPath}/{spks}"):
if file.endswith(".wav"):
file = file[:-4]
audio_path = f"./{wavPath}/{spks}/{file}.wav"
featur_pit = featureInput.compute_f0(audio_path)
coarse_pit = featureInput.coarse_f0(featur_pit)
np.save(
f"{outPath}/{spks}/{file}_pitch.npy",
coarse_pit,
allow_pickle=False,
)
np.save(
f"{outPath}/{spks}/{file}_nsff0.npy",
featur_pit,
allow_pickle=False,
)
path_audio = f"./data/waves/{spks}/{file}.wav"
path_spkid = f"./data/spkid/{spks}.npy"
path_label = (
f"./data/phone/{spks}/{file}.npy" # phone means ppg & hubert
)
path_pitch = f"./data/label/{spks}/{file}_pitch.npy"
path_nsff0 = f"./data/label/{spks}/{file}_nsff0.npy"
print(
f"{path_audio}|{path_spkid}|{path_label}|{path_pitch}|{path_nsff0}",
file=vits_file,
)
vits_file.close()
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