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55 lines
1.7 KiB
55 lines
1.7 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Modified from espnet(https://github.com/espnet/espnet)
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import numpy as np
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def delta(feat, window):
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assert window > 0
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delta_feat = np.zeros_like(feat)
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for i in range(1, window + 1):
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delta_feat[:-i] += i * feat[i:]
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delta_feat[i:] += -i * feat[:-i]
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delta_feat[-i:] += i * feat[-1]
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delta_feat[:i] += -i * feat[0]
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delta_feat /= 2 * sum(i**2 for i in range(1, window + 1))
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return delta_feat
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def add_deltas(x, window=2, order=2):
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"""
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Args:
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x (np.ndarray): speech feat, (T, D).
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Return:
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np.ndarray: (T, (1+order)*D)
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"""
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feats = [x]
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for _ in range(order):
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feats.append(delta(feats[-1], window))
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return np.concatenate(feats, axis=1)
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class AddDeltas():
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def __init__(self, window=2, order=2):
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self.window = window
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self.order = order
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def __repr__(self):
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return "{name}(window={window}, order={order}".format(
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name=self.__class__.__name__, window=self.window, order=self.order)
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def __call__(self, x):
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return add_deltas(x, window=self.window, order=self.order)
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