You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
75 lines
2.3 KiB
75 lines
2.3 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""
|
|
This modules contains normalizers for spectrogram magnitude.
|
|
Normalizers are invertible transformations. They can be used to process
|
|
magnitude of spectrogram before training and can also be used to recover from
|
|
the generated spectrogram so as to be used with vocoders like griffin lim.
|
|
|
|
The base class describe the interface. `transform` is used to perform
|
|
transformation and `inverse` is used to perform the inverse transformation.
|
|
|
|
check issues:
|
|
https://github.com/mozilla/TTS/issues/377
|
|
"""
|
|
import numpy as np
|
|
|
|
__all__ = ["NormalizerBase", "LogMagnitude", "UnitMagnitude"]
|
|
|
|
|
|
class NormalizerBase(object):
|
|
def transform(self, spec):
|
|
raise NotImplementedError("transform must be implemented")
|
|
|
|
def inverse(self, normalized):
|
|
raise NotImplementedError("inverse must be implemented")
|
|
|
|
|
|
class LogMagnitude(NormalizerBase):
|
|
"""
|
|
This is a simple normalizer used in Waveglow, Waveflow, tacotron2...
|
|
"""
|
|
|
|
def __init__(self, min=1e-5):
|
|
self.min = min
|
|
|
|
def transform(self, x):
|
|
x = np.maximum(x, self.min)
|
|
x = np.log(x)
|
|
return x
|
|
|
|
def inverse(self, x):
|
|
return np.exp(x)
|
|
|
|
|
|
class UnitMagnitude(NormalizerBase):
|
|
# dbscale and (0, 1) normalization
|
|
"""
|
|
This is the normalizer used in the
|
|
"""
|
|
|
|
def __init__(self, min=1e-5):
|
|
self.min = min
|
|
|
|
def transform(self, x):
|
|
db_scale = 20 * np.log10(np.maximum(self.min, x)) - 20
|
|
normalized = (db_scale + 100) / 100
|
|
clipped = np.clip(normalized, 0, 1)
|
|
return clipped
|
|
|
|
def inverse(self, x):
|
|
denormalized = np.clip(x, 0, 1) * 100 - 100
|
|
out = np.exp((denormalized + 20) / 20 * np.log(10))
|
|
return out
|