It is well known that parsing accuracy suffers when a model is applied to out-of-domain data. It is also known that the most beneficial data to parse a given domain is data that ...
In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge fr...
We perform a large-scale evaluation of multiple off-the-shelf speech recognizers across diverse domains for virtual human dialogue systems. Our evaluation is aimed at speech recog...
The domain-specific track uses test collections from the social science domain to test monolingual and cross-language retrieval in structured bibliographic databases. Special atte...
Vivien Petras, Stefan Baerisch, Maximilian Stempfh...
After many successes, statistical approaches that have been popular in the parsing community are now making headway into Natural Language Generation (NLG). These systems are aimed...