NAACL
2007
13 years 6 months ago
2007
Collecting supervised training data for automatic speech recognition (ASR) systems is both time consuming and expensive. In this paper we use the notion of virtual evidence in a g...
NAACL
2007
13 years 6 months ago
2007
PropBank has been widely used as training data for Semantic Role Labeling. However, because this training data is taken from the WSJ, the resulting machine learning models tend to...
NAACL
2007
13 years 6 months ago
2007
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
MSV
2007
13 years 6 months ago
2007
Abstract - In this paper, an essential oil extraction system with self-refilling system is modeled based on inputoutput data collected from a dedicated acquisition system. The ARMA...
LREC
2008
13 years 6 months ago
2008
In current phrase-based Statistical Machine Translation systems, more training data is generally better than less. However, a larger data set eventually introduces a larger model ...
LREC
2008
13 years 6 months ago
2008
This paper describes an accurate, extensible method for automatically classifying unknown foreign words that requires minimal monolingual resources and no bilingual training data ...
LREC
2008
13 years 6 months ago
2008
One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. This imbalance...
ICMLA
2007
13 years 6 months ago
2007
Optimal Component Analysis (OCA) is a linear method for feature extraction and dimension reduction. It has been widely used in many applications such as face and object recognitio...
ICMLA
2007
13 years 6 months ago
2007
We study the problem of correcting spelling mistakes in text using memory-based learning techniques and a very large database of token n-gram occurrences in web text as training d...
EMNLP
2007
13 years 6 months ago
2007
We present two machine learning approaches to information extraction from semi-structured documents that can be used if no annotated training data are available, but there does ex...