Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Typically, statistical alignment models are based on single-word dependencies. These models do not include contextual information, which can lead to inadequate alignments. ,  present an approach to include contextual dependencies in the statistical alignment model by using a refined lexicon model. Unlike previous work,  directly integrate this in the EM algorithm of statistical alignment models. Experimental results are given for the French-English Canadian Parliament Hansards task and the Verbmobil task. The evaluation is performed by comparing the obtained alignments with a manually annotated reference alignment.
['Ismael García Varea', 'Franz Josef Och', 'Hermann Ney', 'Francisco Casacuberta']
I am writing a research paper on a idea Improving alignment quality in statistical machine translation using context-dependent maximum entropy models
[{"from": "human", "value": "I am writing a research paper on a idea Improving alignment quality in statistical machine translation using context-dependent maximum entropy models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Typically, statistical alignment models are based on single-word dependencies. These models do not include contextual information, which can lead to inadequate alignments. ,  present an approach to include contextual dependencies in the statistical alignment model by using a refined lexicon model. Unlike previous work,  directly integrate this in the EM algorithm of statistical alignment models. Experimental results are given for the French-English Canadian Parliament Hansards task and the Verbmobil task. The evaluation is performed by comparing the obtained alignments with a manually annotated reference alignment."}]