1. A computerized method for determining when to transfer a user from an automated service to a live agent comprising: a) training a set of classification models using a set of classified historical interactions to perform real-time classification of an interaction wherein said classified historical interactions comprise, at least, prompts provided by the interactive voice response system, transcriptions of statements by a caller derived from an automatic speech recognizer, meanings ascribed to statements made by the caller, and confidence scores for the transcriptions; and b) during an automated interaction between the user and the automated service, using a computer to calculate a log likelihood ratio, using said classification models, to determine whether to transfer said user, from said automated interaction to a live interaction, by computing a log of a prediction that the interaction is good over a prediction that the interaction is bad; wherein: 1) said log likelihood ratio is computed using the formula log(P(x|LM good )/P(x|LM bad )); 2) LM good is a first classification model trained using records of one or more previous interactions classified as good; 3) LM bad is a second classification model trained using records of one or more previous interactions classified as bad; and 4) x is a set of responses made by the user during the interaction.