Neural network method and apparatus

A processor implemented training method, comprising:

• obtaining a scaling factor from a sub-neural network into which a training input is input;
• determining a size of a future context to be considered by a main neural network based on the scaling factor;
• and
• training the main neural network and the sub-neural network such that the main neural network outputs a training output mapped to the training input in response to the training input being input into the main neural network to which the determined size of the future context is applied.

A recognition apparatus, comprising:

• a processor configured to
• provide a voice signal to a main neural network and a sub-neural network,
• obtain a scaling factor by implementing the sub-neural network configured to generate the scaling factor by interpreting the provided voice signal,
• determine a size of a future context, based on the scaling factor, to be considered by the main neural network configured to perform speech recognition, and
• obtain a result of a recognizing of the voice signal by implementing the main neural network with the determined size of the future context.

An electronic device, the electronic device comprising, comprising:

• a speech receiver configured to capture audio;
• a memory storing trained parameters of a main neural network and trained parameters of a sub-neural network;
• and
• a processor configured to apply the trained parameters of the sub-neural network to implement the sub-neural network to which a voice signal derived from the captured audio is input, and to apply the trained parameters of the main neural network to implement the main neural network, to recognize the voice signal, with dynamically adjusted future context consideration based on results of the implementation of the sub-neural network,
• wherein the main neural network includes a recurrent layer configured to consider past context.