Two types of variability can occur in model output: variability between replications and variability within each replication. The objective of the model combined with the type of ...
We propose a novel HMM-based framework to accurately transliterate unseen named entities. The framework leverages features in letteralignment and letter n-gram pairs learned from ...
Bing Zhao, Nguyen Bach, Ian R. Lane, Stephan Vogel
Long-span features, such as syntax, can improve language models for tasks such as speech recognition and machine translation. However, these language models can be difficult to u...
Query translation in Cross Language Information Retrieval (CLIR) can be performed using multiple resources. Previous attempts to combine different translation resources use simple...
Transliteration of new named entity is important for information retrieval that crosses two or multiple language. Rule-based machine transliteration is not satisfactory, since dif...