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ACL
2009
13 years 5 months ago
Predicting Barge-in Utterance Errors by using Implicitly-Supervised ASR Accuracy and Barge-in Rate per User
Modeling of individual users is a promising way of improving the performance of spoken dialogue systems deployed for the general public and utilized repeatedly. We define "im...
Kazunori Komatani, Alexander I. Rudnicky
ACL
2012
11 years 10 months ago
Unsupervised Morphology Rivals Supervised Morphology for Arabic MT
If unsupervised morphological analyzers could approach the effectiveness of supervised ones, they would be a very attractive choice for improving MT performance on low-resource in...
David Stallard, Jacob Devlin, Michael Kayser, Yoon...
ICCV
2011
IEEE
12 years 7 months ago
Strong Supervision From Weak Annotation: Interactive Training of Deformable Part Models
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
Steven Branson, Pietro Perona, Serge Belongie
ACL
2012
11 years 10 months ago
A Graph-based Cross-lingual Projection Approach for Weakly Supervised Relation Extraction
Although researchers have conducted extensive studies on relation extraction in the last decade, supervised approaches are still limited because they require large amounts of trai...
Seokhwan Kim, Gary Geunbae Lee
EMNLP
2009
13 years 5 months ago
Graph Alignment for Semi-Supervised Semantic Role Labeling
Unknown lexical items present a major obstacle to the development of broadcoverage semantic role labeling systems. We address this problem with a semisupervised learning approach ...
Hagen Fürstenau, Mirella Lapata