15. A system including a continuous speech recognition engine hosted on a server that cooperates with a language identification engine, comprising: an input to receive supplied audio files from a client machine over a wide area network to the server hosting the continuous speech recognition engine; and wherein the language identification engine includes a front end module having an input to receive the supplied audio files, a universal phoneme decoder to identify phonemes and phoneme sequences in the audio files in each of two or more candidate languages, and a run-time language identifier module to receive the phonemes and phoneme sequences from the universal phoneme decoder, generate as an output from the universal phoneme decoder a stream of the identified phonemes and phoneme sequences for each of the two or more candidate languages, wherein the streams include a first stream of phonemes from the identified phonemes for a first of the two or more candidate languages, and a second stream of phonemes from the identified phonemes for a second of the two or more candidate languages, determine a confidence rating on an accuracy of an identification of the first candidate language of the two or more candidate languages for the first stream and an accuracy of an identification of the second candidate language of the two or more candidate languages for the second stream, and identify at least one of a particular spoken human language and a specific dialect of a spoken human language being spoken in the supplied audio files based on the confidence ratings.
15. A system including a continuous speech recognition engine hosted on a server that cooperates with a language identification engine, comprising: an input to receive supplied audio files from a client machine over a wide area network to the server hosting the continuous speech recognition engine; and wherein the language identification engine includes a front end module having an input to receive the supplied audio files, a universal phoneme decoder to identify phonemes and phoneme sequences in the audio files in each of two or more candidate languages, and a run-time language identifier module to receive the phonemes and phoneme sequences from the universal phoneme decoder, generate as an output from the universal phoneme decoder a stream of the identified phonemes and phoneme sequences for each of the two or more candidate languages, wherein the streams include a first stream of phonemes from the identified phonemes for a first of the two or more candidate languages, and a second stream of phonemes from the identified phonemes for a second of the two or more candidate languages, determine a confidence rating on an accuracy of an identification of the first candidate language of the two or more candidate languages for the first stream and an accuracy of an identification of the second candidate language of the two or more candidate languages for the second stream, and identify at least one of a particular spoken human language and a specific dialect of a spoken human language being spoken in the supplied audio files based on the confidence ratings. 20. The system of claim 15 , comprising: statistical language models to supply to the run-time language identifier module probabilities of how linguistically likely a particular uttered phoneme identified by the universal phoneme decoder comes from one of the candidate languages, wherein the particular human language being spoken is identified based on the statistical language models.