1. A method comprising: receiving a digital representation of speech; generating a plurality of feature vectors that each model a different portion of an audio waveform from the digital representation of speech during a different period of time, the plurality of feature vectors including a first feature vector and subsequent feature vectors; generating a first posterior probability vector for the first feature vector using a first neural network, the first posterior probability vector comprising one score for each key word or key phrase which the first neural network is trained to identify, wherein the first neural network is trained to identify one or more key words or one or more key phrases; determining whether one of the scores in the first posterior probability vector satisfies a first threshold value using a first posterior handling module; and in response to determining that one of the scores in the first posterior probability vector satisfies the first threshold value and for each of the feature vectors: generating a second posterior probability vector for the respective feature vector using a second neural network, wherein the second neural network is trained to identify the same one or more key words or one or more key phrases as the first neural network, and comprises more inner layer nodes than the first neural network, and the second posterior probability vector comprises one score for each key word or key phrase which the second neural network is trained to identify; determining whether one of the scores in the second posterior probability vector satisfies a second threshold value using a second posterior handling module, the second threshold value being more restrictive than the first threshold value; and in response to determining that one of the scores in the second posterior probability vector satisfies the second threshold value, determining that the digital representation of speech contains a representation of one of the one or more key words or one or more key phrases which the first neural network and the second neural network are trained to identify.