@inproceedings{tiedemann-2010-lingua,
title = "Lingua-Align: An Experimental Toolbox for Automatic Tree-to-Tree Alignment",
author = {Tiedemann, J{\"o}rg},
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/144_Paper.pdf",
abstract = "In this paper we present an experimental toolbox for automatic tree-to-tree alignment based on a binary classification model. The aligner implements a recurrent architecture for structural prediction using history features and a sequential classification procedure. The discriminative base classifier uses a log-linear model in the current setup which enables simple integration of various features extracted from the data. The Lingua-Align toolbox provides a flexible framework for feature extraction including contextual properties and implements several alignment inference procedures. Various settings and constraints can be controlled via a simple frontend or called from external scripts. Lingua-Align supports different treebank formats and includes additional tools for conversion and evaluation. In our experiments we can show that our tree aligner produces results with high quality and outperforms unsupervised techniques proposed otherwise. It also integrates well with another existing tool for manual tree alignment which makes it possible to quickly integrate additional training material and to run semi-automatic alignment strategies.",
}
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<abstract>In this paper we present an experimental toolbox for automatic tree-to-tree alignment based on a binary classification model. The aligner implements a recurrent architecture for structural prediction using history features and a sequential classification procedure. The discriminative base classifier uses a log-linear model in the current setup which enables simple integration of various features extracted from the data. The Lingua-Align toolbox provides a flexible framework for feature extraction including contextual properties and implements several alignment inference procedures. Various settings and constraints can be controlled via a simple frontend or called from external scripts. Lingua-Align supports different treebank formats and includes additional tools for conversion and evaluation. In our experiments we can show that our tree aligner produces results with high quality and outperforms unsupervised techniques proposed otherwise. It also integrates well with another existing tool for manual tree alignment which makes it possible to quickly integrate additional training material and to run semi-automatic alignment strategies.</abstract>
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%0 Conference Proceedings
%T Lingua-Align: An Experimental Toolbox for Automatic Tree-to-Tree Alignment
%A Tiedemann, Jörg
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F tiedemann-2010-lingua
%X In this paper we present an experimental toolbox for automatic tree-to-tree alignment based on a binary classification model. The aligner implements a recurrent architecture for structural prediction using history features and a sequential classification procedure. The discriminative base classifier uses a log-linear model in the current setup which enables simple integration of various features extracted from the data. The Lingua-Align toolbox provides a flexible framework for feature extraction including contextual properties and implements several alignment inference procedures. Various settings and constraints can be controlled via a simple frontend or called from external scripts. Lingua-Align supports different treebank formats and includes additional tools for conversion and evaluation. In our experiments we can show that our tree aligner produces results with high quality and outperforms unsupervised techniques proposed otherwise. It also integrates well with another existing tool for manual tree alignment which makes it possible to quickly integrate additional training material and to run semi-automatic alignment strategies.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/144_Paper.pdf
Markdown (Informal)
[Lingua-Align: An Experimental Toolbox for Automatic Tree-to-Tree Alignment](http://www.lrec-conf.org/proceedings/lrec2010/pdf/144_Paper.pdf) (Tiedemann, LREC 2010)
ACL