shichen.fsc yingda.chen 3 years ago
parent
commit
745bd5a9e0
1 changed files with 0 additions and 62 deletions
  1. +0
    -62
      tests/pipelines/test_automatic_speech_recognition.py

+ 0
- 62
tests/pipelines/test_automatic_speech_recognition.py View File

@@ -53,14 +53,6 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
'checking_item': OutputKeys.TEXT,
'example': 'dataset_example'
},
'test_run_with_ark_dataset': {
'checking_item': OutputKeys.TEXT,
'example': 'dataset_example'
},
'test_run_with_tfrecord_dataset': {
'checking_item': OutputKeys.TEXT,
'example': 'dataset_example'
},
'dataset_example': {
'Wrd': 49532, # the number of words
'Snt': 5000, # the number of sentences
@@ -252,60 +244,6 @@ class AutomaticSpeechRecognitionTest(unittest.TestCase):
model_id=self.am_tf_model_id, audio_in=dataset_path)
self.check_result('test_run_with_wav_dataset_tf', rec_result)

@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
def test_run_with_ark_dataset(self):
'''run with datasets, and audio format is kaldi_ark
datasets directory:
<dataset_path>
test # testsets
data.ark
data.scp
data.text
dev # devsets
data.ark
data.scp
data.text
train # trainsets
data.ark
data.scp
data.text
'''

logger.info('Run ASR test with ark dataset (pytorch)...')
logger.info('Downloading ark testsets file ...')

dataset_path = download_and_untar(
os.path.join(self.workspace, AISHELL1_TESTSETS_FILE),
AISHELL1_TESTSETS_URL, self.workspace)
dataset_path = os.path.join(dataset_path, 'test')

rec_result = self.run_pipeline(
model_id=self.am_pytorch_model_id, audio_in=dataset_path)
self.check_result('test_run_with_ark_dataset', rec_result)

@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
def test_run_with_tfrecord_dataset(self):
'''run with datasets, and audio format is tfrecord
datasets directory:
<dataset_path>
test # testsets
data.records
data.idx
data.text
'''

logger.info('Run ASR test with tfrecord dataset (tensorflow)...')
logger.info('Downloading tfrecord testsets file ...')

dataset_path = download_and_untar(
os.path.join(self.workspace, TFRECORD_TESTSETS_FILE),
TFRECORD_TESTSETS_URL, self.workspace)
dataset_path = os.path.join(dataset_path, 'test')

rec_result = self.run_pipeline(
model_id=self.am_tf_model_id, audio_in=dataset_path)
self.check_result('test_run_with_tfrecord_dataset', rec_result)


if __name__ == '__main__':
unittest.main()

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