Abstract
In order to lighten the heavy computational burden of one-pass lattice-generating algorithms for speech recognition,a fast two-pass decoding algorithm was proposed on the basis of the forward-backward language model.The forward and backward language models were applied to the first and second decoding processes separately.Furthermore,some optimization rules were given to reduce the impact of language model mismatch and to avoid its side-effects on recognition results.The experimental results show that this algorithm quickens the decoding process without decreasing the recognition accurate rate.
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