11. A non-transient computer readable medium programmed with computer readable code that upon execution by a computer processor causes the computer processor to: obtain audio data; segment the audio data into a plurality of utterances; obtain a script model representative of a script text; decode the plurality of utterances by applying the script model to the plurality of utterances; determine if the script text occurred in the audio data from the decoded plurality of utterances; filter the plurality of utterances to include only utterances attributed to a customer service agent; extract acoustic features from the filtered plurality of utterances; use the extracted acoustic features in decoding the plurality of utterances; determine if the audio data is non-compliant; and if so, initiate at least one remedial action that is selected from a graphical display to present on screen guidance to a customer service agent.
11. A non-transient computer readable medium programmed with computer readable code that upon execution by a computer processor causes the computer processor to: obtain audio data; segment the audio data into a plurality of utterances; obtain a script model representative of a script text; decode the plurality of utterances by applying the script model to the plurality of utterances; determine if the script text occurred in the audio data from the decoded plurality of utterances; filter the plurality of utterances to include only utterances attributed to a customer service agent; extract acoustic features from the filtered plurality of utterances; use the extracted acoustic features in decoding the plurality of utterances; determine if the audio data is non-compliant; and if so, initiate at least one remedial action that is selected from a graphical display to present on screen guidance to a customer service agent. 12. The non-transient computer readable medium of claim 11 , wherein execution of the computer readable code further causes the processor to: apply speech analytics to the plurality of utterances to identify at least one event; upon identification of the at least one event select the script model based upon the identified at least one event; and decode a subset of the plurality of utterances occurring after the identified least one event with the selected script model.