Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. One of the methods includes generating, by a speech recognition system, a matrix from a predetermined quantity of vectors that each represent input for a layer of a neural network, generating a plurality of sub-matrices from the matrix, using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network to determine whether an utterance encoded in an audio signal comprises a keyword for which the neural network is trained.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: generating, by a speech recognition system, a matrix from a predetermined quantity of vectors that each represent input for a layer of a neural network; generating a plurality of sub-matrices from the matrix; using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network to determine whether an utterance encoded in an audio signal comprises a keyword for which the neural network is trained. 2. The method of claim 1, wherein generating the plurality of sub-matrices from the matrix comprises generating a plurality of non-overlapping sub-matrices from the matrix. 3. The method of claim 1, wherein: the layer comprises an input layer; and generating the matrix from the predetermined quantity of vectors that each represent input for the layer of the neural network comprises generating the matrix from a predetermined quantity of feature vectors that each model a portion of the audio signal encoding the utterance. 4. The method of claim 1, wherein a size of each of the sub-matrices is the same. 5. The method of claim 1, wherein generating the matrix from the predetermined quantity of vectors comprises generating the matrix from a predetermined quantity of sequential vectors. 6. The method of claim 1, wherein using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network comprises using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network to determine whether the utterance was spoken by a predetermined speaker. 7. The method of claim 1, wherein using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network comprises using each of the sub-matrices as input to a predetermined quantity of nodes in the layer of the neural network. 8. The method of claim 1, wherein using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network comprises using the respective sub-matrix as input to a plurality of adjacent nodes in the layer of the neural network. 9. The method of claim 1, comprising: generating, for each node in the layer of the neural network, output from the node using the respective sub-matrix; determining whether the utterance comprises a keyword using the output from the nodes in the layer; and performing, by a device, an action in response to determining that the utterance comprises a keyword. 10. The method of claim 9, wherein the device includes the speech recognition system. 11. The method of claim 9, wherein performing the action comprises exiting, by the device, a standby state. 12. The method of claim 9, wherein performing the action comprises presenting, by the device, content to a user of the device. 13. The method of claim 9, wherein performing the action comprises performing, by the device, an action for a particular application. 14. The method of claim 13, wherein performing the action for the particular application comprises launching, by the device, the particular application. 15. A computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: generating, by a speech recognition system, a matrix from a predetermined quantity of vectors that each represent input for a layer of a neural network; generating a plurality of sub-matrices from the matrix; using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network to determine whether an utterance encoded in an audio signal comprises a keyword for which the neural network is trained. 16. The computer-readable medium of claim 15, wherein a size of each of the sub-matrices is the same. 17. The computer-readable medium of claim 15, wherein generating the matrix from the predetermined quantity of vectors comprises generating the matrix from a predetermined quantity of sequential vectors. 18. The computer-readable medium of claim 15, wherein using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network comprises using each of the sub-matrices as input to a predetermined quantity of nodes in the layer of the neural network. 19. The computer-readable medium of claim 15, the operations comprising: generating, for each node in the layer of the neural network, output from the node using the respective sub-matrix; determining whether the utterance comprises a keyword using the output from the nodes in the layer; and performing, by a device, an action in response to determining that the utterance comprises a keyword. 20. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: generating, by a speech recognition system, a matrix from a predetermined quantity of vectors that each represent input for a layer of a neural network; generating a plurality of sub-matrices from the matrix; using, for each of the sub-matrices, the respective sub-matrix as input to a node in the layer of the neural network to determine whether an utterance encoded in an audio signal comprises a keyword for which the neural network is trained.