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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 librosa | |
import numpy as np | |
from pypesq import pesq | |
def extract_pesq(audio_ref, audio_deg, **kwargs): | |
"""Extract PESQ for a two given audio. | |
audio1: the given reference audio. It is a numpy array. | |
audio2: the given synthesized audio. It is a numpy array. | |
fs: sampling rate. | |
method: "dtw" will use dtw algorithm to align the length of the ground truth and predicted audio. | |
"cut" will cut both audios into a same length according to the one with the shorter length. | |
""" | |
# Load hyperparameters | |
kwargs = kwargs["kwargs"] | |
fs = kwargs["fs"] | |
method = kwargs["method"] | |
# Load audio | |
if fs != None: | |
audio_ref, _ = librosa.load(audio_ref, sr=fs) | |
audio_deg, _ = librosa.load(audio_deg, sr=fs) | |
else: | |
audio_ref, fs = librosa.load(audio_ref) | |
audio_deg, fs = librosa.load(audio_deg) | |
# Resample | |
if fs != 16000: | |
audio_ref = librosa.resample(audio_ref, orig_sr=fs, target_sr=16000) | |
audio_deg = librosa.resample(audio_deg, orig_sr=fs, target_sr=16000) | |
fs = 16000 | |
# Audio length alignment | |
if len(audio_ref) != len(audio_deg): | |
if method == "cut": | |
length = min(len(audio_ref), len(audio_deg)) | |
audio_ref = audio_ref[:length] | |
audio_deg = audio_deg[:length] | |
elif method == "dtw": | |
_, wp = librosa.sequence.dtw(audio_ref, audio_deg, backtrack=True) | |
audio_ref_new = [] | |
audio_deg_new = [] | |
for i in range(wp.shape[0]): | |
ref_index = wp[i][0] | |
deg_index = wp[i][1] | |
audio_ref_new.append(audio_ref[ref_index]) | |
audio_deg_new.append(audio_deg[deg_index]) | |
audio_ref = np.array(audio_ref_new) | |
audio_deg = np.array(audio_deg_new) | |
assert len(audio_ref) == len(audio_deg) | |
# Compute pesq | |
score = pesq(audio_ref, audio_deg, fs) | |
return score | |