OK, the reason I ask is that a lot of effort has been taken to make sure the use of the lookup list is extremely fast, so unless you have tested the timing and discovered that there is a big difference between the use of your list and the default list, it usually doesn’t accomplish very much to reduce the list, and of course it can potentially lead to less accuracy to remove words. Adding words (as mentioned in the blog post referenced) is the expected/supported usage, since it has the potential to increase accuracy. To add words, just use the same acoustic model that ships with OpenEars 2.5 and add your words to it in the alphabetically-correct location in its language model lookup list.
Can I ask the amount of speed improvement in model generation time you saw by using a lookup list with words removed?
You probably already know this, but to clarify for other readers who find this topic: the lookup lists aren’t the dictionary used during recognition and have no effect at all on recognition speed or accuracy once the model has been generated – the dictionary used during recognition is a newly generated dictionary which is already reduced only to the words needed by the vocabulary. The lookup list is only used very briefly during the generation of the language model.