String Transduction with Target Language Models and Insertion Handling
Table 4: Word-level accuracy (in %) on cognate projection with 100 training instances.
['System', 'EN-DE', 'RU-PL', 'VL-IT']
Of the systems that have no recourse to corpus statistics, the RNN appears crippled by the small training size, while SEQ is competitive with DTL, especially on the difficult EN-DE dataset. On the other hand, the other two systems obtain substantial improvements over DTL, but the gains obtained by DTLM are 2-3 times greater than those obtained by DTL+RR. This demonstrates the advantage of incorporating the language model features directly into the training phase over simple reranking.