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README.md
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README.md
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### Setup
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`. env/bin/activate` to activate the virtualenv.
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### Data Generation
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* update `OUTPUT_NAME` in *speech_samplegen.py* to create the dataset folder with the name
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* `python speech_samplegen.py` generates variants of audio samples
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### Data Preprocessing
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* `python speech_data.py` creates the training-testing data from the generated samples.
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* run `fix_csv(OUTPUT_NAME)` once to create the fixed index of the dataset generated
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* run `generate_sppas_trans(OUTPUT_NAME)` once to create the SPPAS transcription(wav+txt) data
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* run `$ (SPPAS_DIR)/bin/annotation.py -l eng -e csv --ipus --tok --phon --align --align -w ./outputs/OUTPUT_NAME/` once to create the phoneme alignment csv files for all variants.
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* `create_seg_phonpair_tfrecords(OUTPUT_NAME)` creates the tfrecords files
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with the phoneme level pairs of right/wrong stresses
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### Training
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* `python speech_model.py` trains the model with the training data generated.
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* `train_siamese(OUTPUT_NAME)` trains the siamese model with the generated dataset.
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### Testing
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* `python speech_test.py` tests the trained model with the test dataset
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* `evaluate_siamese(TEST_RECORD_FILE,audio_group=OUTPUT_NAME,weights = WEIGHTS_FILE_NAME)`
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the TEST_RECORD_FILE will be under outputs directory and WEIGHTS_FILE_NAME will be under the models directory, pick the most recent weights file.
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@@ -216,6 +216,9 @@ def generate_audio_for_text_list(text_list):
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closer()
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def generate_audio_for_stories():
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'''
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Generates the audio sample variants for the list of words in the stories
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'''
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# story_file = './inputs/all_stories_hs.json'
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story_file = './inputs/all_stories.json'
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stories_data = json.load(open(story_file))
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@@ -225,6 +228,10 @@ def generate_audio_for_stories():
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generate_audio_for_text_list(text_list)
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def generate_test_audio_for_stories(sample_count=0):
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'''
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Picks a list of words from the wordlist that are not in story words
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and generates the variants
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'''
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story_file = './inputs/all_stories_hs.json'
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# story_file = './inputs/all_stories.json'
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stories_data = json.load(open(story_file))
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