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# 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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"""Test error rate."""
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import unittest
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Support paddle 2.x (#538)
* 2.x model
* model test pass
* fix data
* fix soundfile with flac support
* one thread dataloader test pass
* export feasture size
add trainer and utils
add setup model and dataloader
update travis using Bionic dist
* add venv; test under venv
* fix unittest; train and valid
* add train and config
* add config and train script
* fix ctc cuda memcopy error
* fix imports
* fix train valid log
* fix dataset batch shuffle shift start from 1
fix rank_zero_only decreator error
close tensorboard when train over
add decoding config and code
* test process can run
* test with decoding
* test and infer with decoding
* fix infer
* fix ctc loss
lr schedule
sortagrad
logger
* aishell egs
* refactor train
add aishell egs
* fix dataset batch shuffle and add batch sampler log
print model parameter
* fix model and ctc
* sequence_mask make all inputs zeros, which cause grad be zero, this is a bug of LessThanOp
add grad clip by global norm
add model train test notebook
* ctc loss
remove run prefix
using ord value as text id
* using unk when training
compute_loss need text ids
ord id using in test mode, which compute wer/cer
* fix tester
* add lr_deacy
refactor code
* fix tools
* fix ci
add tune
fix gru model bugs
add dataset and model test
* fix decoding
* refactor repo
fix decoding
* fix musan and rir dataset
* refactor io, loss, conv, rnn, gradclip, model, utils
* fix ci and import
* refactor model
add export jit model
* add deploy bin and test it
* rm uselss egs
* add layer tools
* refactor socket server
new model from pretrain
* remve useless
* fix instability loss and grad nan or inf for librispeech training
* fix sampler
* fix libri train.sh
* fix doc
* add license on cpp
* fix doc
* fix libri script
* fix install
* clip 5 wer 7.39, clip 400 wer 7.54, 1.8 clip 400 baseline 7.49
4 years ago
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from deepspeech.utils import error_rate
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class TestParse(unittest.TestCase):
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def test_wer_1(self):
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ref = 'i UM the PHONE IS i LEFT THE portable PHONE UPSTAIRS last night'
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hyp = 'i GOT IT TO the FULLEST i LOVE TO portable FROM OF STORES last '\
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'night'
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word_error_rate = error_rate.wer(ref, hyp)
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self.assertTrue(abs(word_error_rate - 0.769230769231) < 1e-6)
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def test_wer_2(self):
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ref = 'as any in england i would say said gamewell proudly that is '\
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'in his day'
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hyp = 'as any in england i would say said came well proudly that is '\
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'in his day'
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word_error_rate = error_rate.wer(ref, hyp)
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self.assertTrue(abs(word_error_rate - 0.1333333) < 1e-6)
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def test_wer_3(self):
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ref = 'the lieutenant governor lilburn w boggs afterward governor '\
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'was a pronounced mormon hater and throughout the period of '\
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'the troubles he manifested sympathy with the persecutors'
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hyp = 'the lieutenant governor little bit how bags afterward '\
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'governor was a pronounced warman hater and throughout the '\
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'period of th troubles he manifests sympathy with the '\
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'persecutors'
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word_error_rate = error_rate.wer(ref, hyp)
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self.assertTrue(abs(word_error_rate - 0.2692307692) < 1e-6)
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def test_wer_4(self):
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ref = 'the wood flamed up splendidly under the large brewing copper '\
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'and it sighed so deeply'
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hyp = 'the wood flame do splendidly under the large brewing copper '\
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'and its side so deeply'
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word_error_rate = error_rate.wer(ref, hyp)
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self.assertTrue(abs(word_error_rate - 0.2666666667) < 1e-6)
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def test_wer_5(self):
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ref = 'all the morning they trudged up the mountain path and at noon '\
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'unc and ojo sat on a fallen tree trunk and ate the last of '\
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'the bread which the old munchkin had placed in his pocket'
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hyp = 'all the morning they trudged up the mountain path and at noon '\
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'unc in ojo sat on a fallen tree trunk and ate the last of '\
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'the bread which the old munchkin had placed in his pocket'
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word_error_rate = error_rate.wer(ref, hyp)
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self.assertTrue(abs(word_error_rate - 0.027027027) < 1e-6)
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def test_wer_6(self):
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ref = 'i UM the PHONE IS i LEFT THE portable PHONE UPSTAIRS last night'
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word_error_rate = error_rate.wer(ref, ref)
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self.assertEqual(word_error_rate, 0.0)
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def test_wer_7(self):
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ref = ' '
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hyp = 'Hypothesis sentence'
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with self.assertRaises(ValueError):
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word_error_rate = error_rate.wer(ref, hyp)
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def test_cer_1(self):
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ref = 'werewolf'
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hyp = 'weae wolf'
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char_error_rate = error_rate.cer(ref, hyp)
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self.assertTrue(abs(char_error_rate - 0.25) < 1e-6)
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def test_cer_2(self):
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ref = 'werewolf'
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hyp = 'weae wolf'
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char_error_rate = error_rate.cer(ref, hyp, remove_space=True)
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self.assertTrue(abs(char_error_rate - 0.125) < 1e-6)
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def test_cer_3(self):
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ref = 'were wolf'
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hyp = 'were wolf'
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char_error_rate = error_rate.cer(ref, hyp)
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self.assertTrue(abs(char_error_rate - 0.0) < 1e-6)
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def test_cer_4(self):
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ref = 'werewolf'
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char_error_rate = error_rate.cer(ref, ref)
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self.assertEqual(char_error_rate, 0.0)
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def test_cer_5(self):
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ref = u'我是中国人'
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hyp = u'我是 美洲人'
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char_error_rate = error_rate.cer(ref, hyp)
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self.assertTrue(abs(char_error_rate - 0.6) < 1e-6)
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def test_cer_6(self):
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ref = u'我 是 中 国 人'
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hyp = u'我 是 美 洲 人'
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char_error_rate = error_rate.cer(ref, hyp, remove_space=True)
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self.assertTrue(abs(char_error_rate - 0.4) < 1e-6)
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def test_cer_7(self):
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ref = u'我是中国人'
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char_error_rate = error_rate.cer(ref, ref)
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self.assertFalse(char_error_rate, 0.0)
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def test_cer_8(self):
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ref = ''
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hyp = 'Hypothesis'
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with self.assertRaises(ValueError):
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char_error_rate = error_rate.cer(ref, hyp)
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if __name__ == '__main__':
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unittest.main()
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