1. A method of automated evaluation of a transcription quality, the method comprising: obtaining audio data; segmenting the audio data into a plurality of utterances with a voice activity detector operating on a computer processor, wherein each of the plurality of utterances is separated by non-speech segments in the audio data; transcribing the plurality of utterances into at least one word lattice with a large vocabulary continuous speech recognition system operating on the processor; applying, by the processor, a minimum Bayes risk decoder to the at least one word lattice to create at least one confusion network representing the at least one word lattice as a plurality sequential word bins and ε-bins; and calculating, by the processor, at least one conformity ratio from the least one confusion network, wherein the at least one conformity ratio is an automated indication of transcription quality.