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The speech recognition method we chose currently utilizies a speech_recognition module of python that is dependent on google speech to text. It uses internet to comprehend the sound it receives. But the network transfer bottleneck slows down the process.
In the CNMP training code located refering to the third experiment refered to in paper, keras is used for training. Spesifically, model.fit encapsulates the whole training process. We are doing the training on GPU and we observe that after a treshold iteration index, due to memory bloat out program gets killed.
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