9th Annual Conference of the International Speech Communication Association

Brisbane, Australia
September 22-26, 2008

Parsing with Subdomain Instance Weighting from Raw Corpora

Barbara Plank (1), Khalil Sima'an (2)

(1) University of Groningen, The Netherlands
(2) University of Amsterdam, The Netherlands

The treebanks that are used for training statistical parsers consist of hand-parsed sentences from a single source/domain like newspaper text. However, newspaper text concerns different subdomains of language use (e.g. finance, sports, politics, music), which implies that the statistics gathered by generative statistical parsers are averages over subdomain statistics. In this paper we explore a method, subdomain instance-weighting, that exploits raw subdomain corpora for introducing subdomain statistics into a state-of-the-art generative parser. We employ instance-weighting for creating an ensemble of subdomain specific versions of the parser, and explore methods for amalgamating their predictions. Our experiments show that subdomain statistics extracted from raw corpora can even improve the quality of the n-best lists of a formidable, state-of-the-art parser.

Full Paper

Bibliographic reference.  Plank, Barbara / Sima'an, Khalil (2008): "Parsing with subdomain instance weighting from raw corpora", In INTERSPEECH-2008, 2540.