Detection of acoustic impulse events in voice applications using a neural network

An integrated circuit for implementing at least a portion of an audio device, comprising:

• an audio input for receiving audio information to be reproduced;
• an audio output configured to reproduce the audio information by generating an audio output signal for communication to at least one transducer of the audio device;
• a microphone input configured to receive an input signal indicative of ambient sound external to the audio device;
• and
• a processor configured to implement an impulsive noise detector comprising:
• a plurality of processing blocks for determining a feature vector based on characteristics of the input signal, wherein the feature vector comprises a statistic indicative of a degree of temporal modulation of a signal spectrum of the input signal;
• a pre-processing block configured to:
• augment the feature vector with at least one previous frame of the input signal to generate an augmented feature vector, wherein the augmented feature vector has an increased feature redundancy relative to the feature vector based on temporal correlations between frames;
• and
• reduce the feature redundancy of the augmented feature vector via feature dimension reduction;
• and
• a neural network for determining, based on the augmented feature vector, whether an impulsive event comprises a speech event or a noise event, wherein the neural network is trained with an augmented training data set based on amplitude, time, and frequency scaling of an initial training data set of impulsive noise events;
• wherein the processor is further configured to modify the generated audio output signal based on the determination of the neural network.