Patent ID: 9728184
Date: 2017-08-08
CPC Classifications: G06N,G10L

Claim:
1. A method comprising: accessing a Deep Neural Network (DNN) model that includes a weight matrix and layers comprising: determining whether the weight matrix is a weight matrix having at least as many parameters as a weight matrix immediately preceding the output layer; upon determining that the weight matrix has at least as many parameters as a weight matrix immediately preceding the output layer, reducing a sparseness of the weight matrix in the DNN model, wherein reducing the sparseness comprises executing decomposition processing of the weight matrix to generate two smaller matrices from the weight matrix, wherein the decomposition processing comprises applying Singular Value Decomposition (SVD) to the weight matrix; restructuring the DNN model based on the executed decomposition processing, wherein the restructuring further comprises modifying the plurality of values coupling the first and second hidden layers of the DNN model by replacing the weight matrix with the two smaller matrices; providing the restructured DNN model; receiving an utterance; and processing the received utterance using the restructured DNN model.