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Keyword Spotting (KWS) provides the start signal of ASR problem, and thus itis essential to ensure a high recall rate. However, its real-time propertyrequires low computation complexity. This contradiction inspires people to finda suitable model which is small enough to perform well in multi environments.To deal with this contradiction, we implement the Hierarchical NeuralNetwork(HNN), which is proved to be effective in many speech recognitionproblems. HNN outperforms traditional DNN and CNN even though its model sizeand computation complexity are slightly less. Also, its simple topologystructure makes easy to deploy on any device.

Hierarchical Neural Network Architecture In Keyword Spotting