Using the same notation proposed in (Moschitti et al., 2007) and , our SCLM trains joint probability P (W, C) of word and concept sequences from an annotated corpus: where Since we use a 3-gram conceptual language model, the history h i is All the steps of the translation process described here and above are implemented as Finite State Transducers (FST) using the AT&T FSM/GRM tools and the SRILM (Stolcke, 2002) tools.
the SCLM is trained using SRILM tools and then converted to an FST.