Keyword search method based on unified representation
A keyword and characterization technology, applied in audio data retrieval, metadata audio data retrieval, special data processing applications, etc., can solve the problems of modeling, use, and maintenance inconvenience, and achieve the effect of convenient modeling
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[0018] The preferred embodiments will be described in detail below in conjunction with the accompanying drawings.
[0019] Step 1: Use a large amount of speech data to train a neural network speech autoencoder with a bottleneck layer: the training data can be mixed data of various languages, and no content labeling is required; the input of the autoencoder is a speech (or feature), and the output It is the same segment of speech (or features); the neural network can adopt deep neural network, convolutional neural network or recursive neural network, the middle is a bottleneck layer with a small number of nodes, and the input and output are symmetrical structures; the training goal is to make The mean square error between the output speech (or feature) and the input speech (or feature) is the smallest;
[0020] Step 2: Use the bottleneck layer of the neural network speech autoencoder as the output layer to obtain the acoustic representation vector extractor: keep the part from ...
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