Method And System For Speech Enhancement

A computer system for training a neural network for de-noising audio enhancement, the computer system comprising:

• a processor;
• and
• a memory with computer code instructions stored thereon, the processor and the memory, with the computer code instructions being configured to cause the system to:
• create simulated noisy speech data from high quality speech data;
• and
• perform training on a neural network using the high quality speech data and the simulated noisy speech data to train the neural network to create de-noised speech data given noisy speech data, wherein performing the training includes minimizing errors in the neural network according to at least one of:
• a decoding error of an Automatic Speech Recognition (ASR) system processing current de-noised speech data results that are generated by the neural network during the training;
• and
• spectral distance between the high quality speech data and the current de-noised speech data results that are generated by the neural network during the training.

A non-transitory computer program product for training a neural network for de-noising audio enhancement, the computer program product comprising:

• one or more computer-readable storage devices and program instructions stored on at least one of the one or more storage devices, the program instructions, when loaded and executed by a processor, cause an apparatus associated with the processor to:
• create simulated noisy speech data from high quality speech data;
• and
• perform training on a neural network using the high quality speech data and the simulated noisy speech data to train the neural network to create de-noised speech data given noisy speech data, wherein performing the training includes minimizing errors in the neural network according to at least one of:
• a decoding error of an Automatic Speech Recognition (ASR) system processing current de-noised speech data results that are generated by the neural network during the training;
• and
• spectral distance between the high quality speech data and the current de-noised speech data results that are generated by the neural network during the training.