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Speech is the vocalized form of communication used by humans and some animals. It is based upon the syntactic combination of items drawn from the lexicon. Each spoken word is created out of the phonetic combination of a limited set of vowel and consonant speech sound units (phonemes). Here, the authors propose a deep learning model used on tensor flow speech recognition dataset, which consist of 30 words. Here, 2D convolutional neural network (CNN) model is used for understanding simple spoken commands using the speech commands dataset by tensor flow. Dataset is divided into 70% training and 30% testing data. While running the algorithm for three epochs average accuracy of 92.7% is achieved.

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