Classifying segments of speech based on acoustic features and context

A system comprising:

• a microphone configured to receive an input speech;
• an analog to digital (A/D) converter configured to convert the input speech from an analog form to a digital form and generate a digitized speech including a plurality of segments having acoustic features;
• a memory storing an executable code;
• and
• a hardware processor executing the executable code to:
• extract a plurality of acoustic feature vectors from the first segment of the plurality of segments of the digitized speech;
• determine, based on the plurality of acoustic feature vectors, a plurality of probability distribution vectors corresponding to the probabilities that the first segment of the digitized speech includes each of a first keyword, a second keyword, both the first keyword and the second keyword, a background, and a social speech;
• assign a first classification label to the first segment based on an analysis of the plurality of probability distribution vectors of one or more segments preceding the first segment and the probability distribution vectors of the first segment, wherein the assigning of the first classification label to the first segment includes distinguishing between the first keyword and an audio event that is one of the social speech and the background;
• and
• execute a first action associated with a first command when the first classification label includes the first command.