Abstract: Implementations described herein identify and correct automatic speech recognition (ASR) misrecognitions. For example, on-device processor(s) of a client device may generate a predicted textual segment that is predicted to correspond to spoken utterance of a user of the client device, and may receive further input that modifies the predicted textual segment to an alternate textual segment. Further, the on-device processor(s) may store these textual segments in on-device storage as a candidate correction pair, and transmit the candidate correction pair to a remote system. Moreover, remote processor(s) of the remote system may determine that the candidate correction pair is an actual correction pair, and may cause client devices to generate updates for a global ASR model for the candidate correction pair. Additionally, the remote processor(s) may distribute the global ASR model to the client devices and/or additional client devices.

Abstract: A method and system for augmenting a neural network is provided herein. The method comprises connecting an input layer to a pre-input layer. The method further comprises joining a hidden layer to the input layer. The method comprises linking an output layer to the hidden layer. The method further comprises connecting a layer for computing physics equations to the output layer. The neural network system further comprising, an input layer, a hidden layer connected to the input layer and an output layer joined to the hidden layer. The system further comprising a layer for computing physics equations connected to the output layer and a pre-input layer attached to the input layer.