首页>
外国专利>
TIME-FREQUENCY CONVOLUTIONAL NEURAL NETWORK WITH BOTTLENECK ARCHITECTURE FOR QUERY-BY-EXAMPLE PROCESSING
TIME-FREQUENCY CONVOLUTIONAL NEURAL NETWORK WITH BOTTLENECK ARCHITECTURE FOR QUERY-BY-EXAMPLE PROCESSING
展开▼
机译:带有Botneteck架构的时频卷积神经网络用于按样例查询处理
展开▼
页面导航
摘要
著录项
相似文献
摘要
A computing system determines whether a reference audio signal contains a query. A time-frequency convolutional neural network (TFCNN) comprises a time and frequency convolutional layers and a series of additional layers, which include a bottleneck layer. The computation engine applies the TFCNN to samples of a query utterance at least through the bottleneck layer. A query feature vector comprises output values of the bottleneck layer generated when the computation engine applies the TFCNN to the samples of the query utterance. The computation engine also applies the TFCNN to samples of the reference audio signal at least through the bottleneck layer. A reference feature vector comprises output values of the bottleneck layer generated when the computation engine applies the TFCNN to the samples of the reference audio signal. The computation engine determines at least one detection score based on the query feature vector and the reference feature vector.
展开▼