16. The method of claim 15, wherein the feature space for the model for non-speech is created by: taking a window of input speech every 10 milliseconds and computing a vector comprising the energy or log energy in logarithmically spaced frequency bands on that window, the feature being the variance across the dimensions of the vector.
15. A method for transcribing a segment of data that includes speech in one or more environments and non-speech data, comprising: inputting the data to a segmenter and producing a series of segments, each segment being given a type identifier tag selected from a predetermined set of classes, wherein it is assumed that the input data is produced by a parallel combination of models, each model corresponding to one of the predetermined classes, the identifier tag assigned to a segment being the class identifier tag of the model that gives the segment the highest probability, subject to certain constraints, wherein a number of classes that the acoustic input can be classified into are identified that represent the most acoustically dissimilar classes possible and, wherein the process of creating the models comprises identifying a feature space for the individual predetermined classes; and transcribing each type identifier tagged segment using a specific system created for that type.