System and method for multi-channel multi-feature speech/noise classification for noise suppression

A multi-channel noise suppression system comprising:

• a plurality of input channels;
• and
• a noise suppression module configured to:
• measure signal classification features for an audio signal frame input from each of the plurality of input channels;
• calculate a feature-based speech probability for each of the measured signal classification features of each of the plurality of input channels;
• generate a speech probability for each of the plurality of input channels by combining the feature-based speech probabilities of the input channel;
• and
• generate a combined speech probability for the audio signal frame using at least one of the speech probabilities of the plurality of input channels and an additive model for a top layer of a probabilistic layered network model.

A method for classifying an audio signal received at a noise suppression module via a plurality of input channels as speech or noise, the method comprising:

• measuring, for each of the plurality of channels, signal classification features for a frame of the signal input from the channel;
• determining, for each of the measured signal classification features of each of the plurality of channels, a first classification state for the signal based on the measured signal classification feature;
• determining, for each of the plurality of channels, a second classification state for the signal by combining the first classification states of the channel using a probabilistic layered network model with an additive model as a top layer;
• and
• classifying the signal as speech or noise based on the second classification states of the plurality of channels.