17. The non-transitory computer-readable medium of claim 15 , wherein the operations comprise: obtaining, by the computing device access to the neural network; for each of multiple utterances of the particular speaker: inputting, by the computing device, speech data corresponding to the respective utterance to the neural network; and generating, by the computing device, a representation of activations occurring at the particular layer of the neural network in response to the speech data corresponding to the respective utterance; combining, by the computing device, the generated representations of activations occurring at the particular layer of the neural network in response to speech data corresponding to each of the multiple utterances of the particular speaker; and using, by the computing device, the combination of generated representations of activations occurring at the particular layer of the neural network in response to speech data corresponding to each of the multiple utterances of the particular speaker as the reference representation.
15. A non-transitory computer-readable medium storing software having stored thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: inputting, by a computing device, speech data that corresponds to a particular utterance of a particular speaker to a neural network having parameters trained based on propagation between an input layer and an output layer through one or more hidden layers located between the input layer and the output layer, wherein the one or more hidden layers were trained using utterances of multiple speakers, and wherein the multiple speakers do not include the particular speaker; generating, by the computing device and in response to inputting the speech data that corresponds to the particular utterance to the neural network, a representation of activations occurring at a particular layer of the neural network that was trained as one of the hidden layers located between the input layer and the output layer; comparing, by the computing device, the generated representation of activations occurring at the particular layer of the neural network in response to the speech data that corresponds to the particular utterance with a reference representation of activations occurring at the particular layer of the neural network in response to speech data that corresponds to one or more past utterances of the particular speaker; based on comparing the generated representation and the reference representation, determining, by the computing device, that the particular utterance was likely spoken by the particular speaker; and providing, by the computing device, access to the computing device based on determining that the particular utterance was likely spoken by the particular speaker.