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# Copyright (c) 2023 Amphion. | |
# | |
# This source code is licensed under the MIT license found in the | |
# LICENSE file in the root directory of this source tree. | |
import torch | |
import librosa | |
from utils.util import JsonHParams | |
from utils.f0 import get_f0_features_using_parselmouth, get_pitch_sub_median | |
from utils.mel import extract_mel_features | |
def extract_spr( | |
audio, | |
fs=None, | |
hop_length=256, | |
win_length=1024, | |
n_fft=1024, | |
n_mels=128, | |
f0_min=37, | |
f0_max=1000, | |
pitch_bin=256, | |
pitch_max=1100.0, | |
pitch_min=50.0, | |
): | |
"""Compute Singing Power Ratio (SPR) from a given audio. | |
audio: path to the audio. | |
fs: sampling rate. | |
hop_length: hop length. | |
win_length: window length. | |
n_mels: number of mel filters. | |
f0_min: lower limit for f0. | |
f0_max: upper limit for f0. | |
pitch_bin: number of bins for f0 quantization. | |
pitch_max: upper limit for f0 quantization. | |
pitch_min: lower limit for f0 quantization. | |
""" | |
# Load audio | |
if fs != None: | |
audio, _ = librosa.load(audio, sr=fs) | |
else: | |
audio, fs = librosa.load(audio) | |
audio = torch.from_numpy(audio) | |
# Initialize config | |
cfg = JsonHParams() | |
cfg.sample_rate = fs | |
cfg.hop_size = hop_length | |
cfg.win_size = win_length | |
cfg.n_fft = n_fft | |
cfg.n_mel = n_mels | |
cfg.f0_min = f0_min | |
cfg.f0_max = f0_max | |
cfg.pitch_bin = pitch_bin | |
cfg.pitch_max = pitch_max | |
cfg.pitch_min = pitch_min | |
# Extract mel spectrograms | |
cfg.fmin = 2000 | |
cfg.fmax = 4000 | |
mel1 = extract_mel_features( | |
y=audio.unsqueeze(0), | |
cfg=cfg, | |
).squeeze(0) | |
cfg.fmin = 0 | |
cfg.fmax = 2000 | |
mel2 = extract_mel_features( | |
y=audio.unsqueeze(0), | |
cfg=cfg, | |
).squeeze(0) | |
f0 = get_f0_features_using_parselmouth( | |
audio, | |
cfg, | |
) | |
# Mel length alignment | |
length = min(len(f0), mel1.shape[-1]) | |
f0 = f0[:length] | |
mel1 = mel1[:, :length] | |
mel2 = mel2[:, :length] | |
# Compute SPR | |
res = [] | |
for i in range(mel1.shape[-1]): | |
if f0[i] <= 1: | |
continue | |
chunk1 = mel1[:, i] | |
chunk2 = mel2[:, i] | |
max1 = max(chunk1.numpy()) | |
max2 = max(chunk2.numpy()) | |
tmp_res = max2 - max1 | |
res.append(tmp_res) | |
if len(res) == 0: | |
return False | |
else: | |
return sum(res) / len(res) | |