1. A method for automatically generating acoustic models for speech recognition, comprising the steps of: utilizing stored training material, which includes recorded utterances in a first language, in conjunction with trained acoustic models of the first language; deriving a time alignment between analysis frames, for the recorded utterances, and phonemes of the first language utilizing a phoneme-based training algorithm; deriving associations between the analysis frames and phonemes of a second language utilizing a second language phoneme recognizer on the recorded utterances in the first language; retrieving the associations between the analysis frames and individual phoneme symbols for both the first language and the second language, wherein such retrieved associations are stored; statistically analyzing the associations to determine a best phoneme to phoneme (P2P) mapping between the first and second language phonetic inventories; transcribing all words in the first language phonetic inventory, utilizing the best P2P mapping, utilizing phonemes from the second language phonetic inventory; and generating a new phonetic inventory utilizing the transcribed words of the first language phonetic inventory.