Referential semantic language modeling for data-poor domains
Stephen Wu, Lane Schwartz, William Schuler · IEEE International Conference on Acoustics Speech and Signal Processing · 2008
This paper describes a referential semantic language model that achieves accurate recognition in user-defined domains with no available domain-specific training corpora. This model is interesting in that, unlike similar recent systems, it exploits context dynamically, using incremental processing and limited stack memory of an HMM-like time series model to constrain search.