To deal with phonological variability alternate pronunciations are included in the lexicon, and optional phonological rules are applied during training and recognition. A trigram LM is used in a second acoustic decoding pass which makes use of the word graph generated using the bigram LM [6] . Experimental results are reported on the ARPA Wall Street Journal (WSJ) <cite>[19]</cite> and BREF [14] corpora, using for both corpora over 37k utterances for acoustic training and more than 37 million words of newspaper text for language model training. It is shown that for both corpora increasing the amount of training utterances by an order of magnitude reduces the word error by about 30%. The use of a trigram LM in a second pass also gives an error reduction of 20% to 30%.