Azalea (on HyDEV-Daisy)
14 lines
546 B
Python
14 lines
546 B
Python
import os
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import numpy as np
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from inaSpeechSegmenter import tf_mfcc
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from formants import predict_from_times
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if __name__ == '__main__':
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os.environ['XLA_FLAGS'] = '--xla_gpu_cuda_data_dir=/opt/cuda'
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# predict_from_times('data/VT 150hz baseline example.mp3', 'data/VT Predictions.csv', 0, 1)
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# tf_mfcc.power_spectrum(np.zeros(1024, dtype=np.int16), 1024, 512)
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predict_from_times('data/Example-f32le.wav', 'data/Example-F32-Predictions.csv', 0, 1)
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# predict_from_times('data/Example.wav', 'data/Example-Predictions.csv', 0, 1)
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