X. Zhang. International Journal on Natural Language Computing (IJNLC), 5 (5):
1-12(October 2016)
Abstract
Increasing interpreting needs a more objective and automatic measurement. We hold a basic idea that 'translating means translating meaning' in that we can assessment interpretation quality by comparing the meaning of the interpreting output with the source input. That is, a translation unit of a 'chunk' named
Frame which comes from frame semantics and its components named Frame Elements (FEs) which comes from Frame Net are proposed to explore their matching rate between target and source texts. A case study in this paper verifies the usability of semi-automatic graded semantic-scoring measurement for human
simultaneous interpreting and shows how to use frame and FE matches to score. Experiments results show that the semantic-scoring metrics have a significantly correlation coefficient with human judgment.
%0 Journal Article
%1 noauthororeditor
%A Zhang, Xiaojun
%D 2016
%E Ozcan, Abdul Kadir
%J International Journal on Natural Language Computing (IJNLC)
%K Element, Frame Frame, Interpreting Quality, Semantics
%N 5
%P 1-12
%T SEMI-AUTOMATIC SIMULTANEOUS INTERPRETING QUALITY EVALUATION
%U http://airccse.org/journal/ijnlc/current.html
%V 5
%X Increasing interpreting needs a more objective and automatic measurement. We hold a basic idea that 'translating means translating meaning' in that we can assessment interpretation quality by comparing the meaning of the interpreting output with the source input. That is, a translation unit of a 'chunk' named
Frame which comes from frame semantics and its components named Frame Elements (FEs) which comes from Frame Net are proposed to explore their matching rate between target and source texts. A case study in this paper verifies the usability of semi-automatic graded semantic-scoring measurement for human
simultaneous interpreting and shows how to use frame and FE matches to score. Experiments results show that the semantic-scoring metrics have a significantly correlation coefficient with human judgment.
@article{noauthororeditor,
abstract = {Increasing interpreting needs a more objective and automatic measurement. We hold a basic idea that 'translating means translating meaning' in that we can assessment interpretation quality by comparing the meaning of the interpreting output with the source input. That is, a translation unit of a 'chunk' named
Frame which comes from frame semantics and its components named Frame Elements (FEs) which comes from Frame Net are proposed to explore their matching rate between target and source texts. A case study in this paper verifies the usability of semi-automatic graded semantic-scoring measurement for human
simultaneous interpreting and shows how to use frame and FE matches to score. Experiments results show that the semantic-scoring metrics have a significantly correlation coefficient with human judgment. },
added-at = {2016-12-14T04:46:32.000+0100},
author = {Zhang, Xiaojun},
biburl = {https://www.bibsonomy.org/bibtex/27675a06bd41aa3201ed212b836d5a709/laimbee},
editor = {Ozcan, Abdul Kadir},
interhash = {c7690ef82c9a798957dd644eb753131f},
intrahash = {7675a06bd41aa3201ed212b836d5a709},
journal = {International Journal on Natural Language Computing (IJNLC)},
keywords = {Element, Frame Frame, Interpreting Quality, Semantics},
month = {October},
number = 5,
pages = {1-12},
timestamp = {2016-12-14T04:46:32.000+0100},
title = {SEMI-AUTOMATIC SIMULTANEOUS INTERPRETING QUALITY EVALUATION},
url = {http://airccse.org/journal/ijnlc/current.html},
volume = 5,
year = 2016
}