Indeed there is work in the literature that shows that various topic models, latent or otherwise, can be useful for improving lan-guage model perplexity and word error rate (Khudanpur and Wu, 1999;Chen, 2009;Naptali et al., 2012).
given the preponderance of highly frequent non-content words in the computation of a corpus' WER, it's not clear that a 1-2% improvement in WER would translate into an improvement in term detection.