In addition , combination of the <term> training speakers </term> is done by averaging the <term> statistics > </term> of <term> independently trained models </term> rather than the usual pooling of all the <term> speech data </term> from many <term> speakers </term> prior to <term> training </term> .
<term> Honorifics </term> are used extensively in <term> Japanese </term> , reflecting the social relationship ( e.g. social ranks and age ) of the <term> referents </term> .
We present an efficient algorithm for the <term> redundancy elimination problem </term> : Given an <term> underspecified semantic representation ( USR ) </term> of a <term> scope ambiguity </term> , compute an <term> USR </term> with fewer mutually <term> equivalent readings </term> .
<term> Task-based evaluation </term> using <term> Arabic information retrieval </term> indicates an improvement of 22-38 % in <term> average precision </term> over <term> unstemmed text </term> , and 96 % of the performance of the proprietary <term> stemmer </term> above .
In this paper <term> discourse segments </term> are defined and a method for <term> discourse segmentation </term> primarily based on <term> abduction </term> of <term> temporal relations </term> between <term> segments </term> is proposed .
For <term> pragmatics processing </term> , we describe how the method of <term> abductive inference </term> is inherently robust , in that an interpretation is always possible , so that in the absence of the required <term> world knowledge </term> , performance degrades gracefully .
The <term> attentional state </term> is an abstraction of the <term> focus of attention </term> of the <term> participants </term> as the <term> discourse </term> unfolds .
This paper introduces a method for <term> computational analysis of move structures </term> in <term> abstracts </term> of <term> research articles </term> .
We summarize the motivation for this effort , the goals , the implementation of a <term> multi-site data collection paradigm </term> , and the accomplishments of <term> MADCOW </term> in monitoring the <term> collection </term> and distribution of 12,000 <term> utterances </term> of <term> spontaneous speech </term> from five sites for use in a <term> multi-site common evaluation of speech , natural language and spoken language
This paper gives an overall account of a prototype <term> natural language question answering system </term> , called <term> Chat-80 </term> .
The <term> classification accuracy </term> of the <term> method </term> is evaluated on three different <term> spoken language system domains </term> .
This paper proposes a new methodology to improve the <term> accuracy </term> of a <term> term aggregation system </term> using each author 's text as a coherent <term> corpus </term> .
Our proposed method improves the <term> accuracy </term> of our <term> term aggregation system </term> , showing that our approach is successful .
Surprisingly however , the <term> WSD </term><term> accuracy </term> of <term> SMT models </term> has never been evaluated and compared with that of the dedicated <term> WSD models </term> .
We present controlled experiments showing the <term> WSD </term><term> accuracy </term> of current typical <term> SMT models </term> to be significantly lower than that of all the dedicated <term> WSD models </term> considered .
tech,12-5-H01-1041,bq ( iii ) <term> Rapid system development </term> and porting to new <term> domains </term> via <term> knowledge-based automated acquisition of grammars </term> .
tech,19-1-P03-1068,bq We describe the ongoing construction of a large , <term> semantically annotated corpus </term> resource as reliable basis for the large-scale <term> acquisition of word-semantic information </term> , e.g. the construction of <term> domain-independent lexica </term> .
Manual acquisition of <term> semantic constraints </term> in broad domains is very expensive .
First , we investigate how well the <term> addressee </term> of a <term> dialogue act </term> can be predicted based on <term> gaze </term> , <term> utterance </term> and <term> conversational context features </term> .
The principle advantage of this approach is that knowledge concerning translation equivalence of expressions may be directly exploited , obviating the need for answers to <term> semantic questions </term> that we do not yet have .
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