1. A method for automatic speech recognition, wherein the method comprises: obtaining at least one language model word; determining an acoustic similarity between the at least one language model word and each rule-based grammar word in a set of multiple rule-based grammar words; and increasing a transition cost to the at least one language model word proportionally to the acoustic similarity between the at least one language model word and at least one of the multiple rule-based grammar words to generate a modified language model for automatic speech recognition, wherein said increasing the transition cost to the at least one language model word comprises increasing a likelihood of selecting at least one of the multiple rule-based grammar words over the at least one language model word as a recognition output; wherein at least one of the steps is carried out by a computer device.
1. A method for automatic speech recognition, wherein the method comprises: obtaining at least one language model word; determining an acoustic similarity between the at least one language model word and each rule-based grammar word in a set of multiple rule-based grammar words; and increasing a transition cost to the at least one language model word proportionally to the acoustic similarity between the at least one language model word and at least one of the multiple rule-based grammar words to generate a modified language model for automatic speech recognition, wherein said increasing the transition cost to the at least one language model word comprises increasing a likelihood of selecting at least one of the multiple rule-based grammar words over the at least one language model word as a recognition output; wherein at least one of the steps is carried out by a computer device. 2. The method of claim 1 , wherein increasing a transition cost to the at least one language model comprises computing the increase in the transition cost as a function of the acoustic similarity.