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This commit is contained in:
JinZr 2024-10-12 15:33:38 +08:00
parent df87a0fe2c
commit 5492a6a5e2
2 changed files with 15 additions and 16 deletions
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22
egs/libritts/CODEC/encodec/loss.py
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@ -1,8 +1,19 @@
# Modified from egs/ljspeech/TTS/vits/loss.py by: Zengrui JIN (Tsinghua University)
# original implementation is from https://github.com/espnet/espnet/blob/master/espnet2/gan_tts/hifigan/loss.py
# Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encodec-related loss modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
from typing import List, Tuple, Union
import torch
import torch.nn.functional as F
from lhotse.features.kaldi import Wav2LogFilterBank
from torchaudio.transforms import MelSpectrogram
@ -225,15 +236,6 @@ class MelSpectrogramReconstructionLoss(torch.nn.Module):
self.wav_to_specs = []
for i in range(5, 12):
s = 2**i
# self.wav_to_specs.append(
# Wav2LogFilterBank(
# sampling_rate=sampling_rate,
# frame_length=s,
# frame_shift=s // 4,
# use_fft_mag=use_fft_mag,
# num_filters=n_mels,
# )
# )
self.wav_to_specs.append(
MelSpectrogram(
sample_rate=sampling_rate,

9
egs/libritts/CODEC/encodec/train.py
View File

@ -186,12 +186,11 @@ def get_params() -> AttributeDict:
"env_info": get_env_info(),
"sampling_rate": 24000,
"audio_normalization": False,
"chunk_size": 1.0, # in seconds
"lambda_adv": 3.0, # loss scaling coefficient for adversarial loss
"lambda_wav": 0.1, # loss scaling coefficient for waveform loss
"lambda_feat": 4.0, # loss scaling coefficient for feat loss
"lambda_rec": 1.0, # loss scaling coefficient for reconstruction loss
"lambda_com": 1.0, # loss scaling coefficient for commitment loss
"lambda_com": 1000.0, # loss scaling coefficient for commitment loss
}
)
@ -342,12 +341,10 @@ def prepare_input(
if is_training:
audio_dims = audio.size(-1)
start_idx = random.randint(
0, max(0, audio_dims - params.chunk_size * params.sampling_rate)
)
start_idx = random.randint(0, max(0, audio_dims - params.sampling_rate))
audio = audio[:, start_idx : params.sampling_rate + start_idx]
else:
# NOTE: a very coarse setup
# NOTE(zengrui): a very coarse setup
audio = audio[
:, params.sampling_rate : params.sampling_rate + params.sampling_rate
]