6 papers
Robust Probabilistic Predictive Syntactic Processing
Brian Roark
This thesis presents a broad-coverage probabilistic top-down parser, and its application to the problem of language modeling for speech recognition. The parser builds fully connect…
Probabilistic top-down parsing and language modeling
Brian Roark
This paper describes the functioning of a broad-coverage probabilistic top-down parser, and its application to the problem of language modeling for speech recognition. The paper fi…
Measuring efficiency in high-accuracy, broad-coverage statistical parsing
Brian Roark, Eugene Charniak
Very little attention has been paid to the comparison of efficiency between high accuracy statistical parsers. This paper proposes one machine-independent metric that is general en…
Noun-phrase co-occurrence statistics for semi-automatic semantic lexicon construction
Brian Roark, Eugene Charniak
Generating semantic lexicons semi-automatically could be a great time saver, relative to creating them by hand. In this paper, we present an algorithm for extracting potential entr…
Compact non-left-recursive grammars using the selective left-corner transform and factoring
Mark Johnson, Brian Roark
The left-corner transform removes left-recursion from (probabilistic) context-free grammars and unification grammars, permitting simple top-down parsing techniques to be used. Unfo…
Efficient probabilistic top-down and left-corner parsing
Brian Roark, Mark Johnson
This paper examines efficient predictive broad-coverage parsing without dynamic programming. In contrast to bottom-up methods, depth-first top-down parsing produces partial parses…