Lexical vagueness handling using fuzzy logic in human robot interaction

2.50
Hdl Handle:
http://hdl.handle.net/10547/294440
Title:
Lexical vagueness handling using fuzzy logic in human robot interaction
Authors:
Guo, Xiao
Abstract:
Lexical vagueness is a ubiquitous phenomenon in natural language. Most of previous works in natural language processing (NLP) consider lexical ambiguity as the main problem in natural language understanding rather than lexical vagueness. Lexical vagueness is usually considered as a solution rather than a problem in natural language understanding since precise information is usually failed to be provided in conversations. However, lexical vagueness is obviously an obstacle in human robot interaction (HRI) since the robots are expected to precisely understand their users' utterances in order to provide reliable services to their users. This research aims to develop novel lexical vagueness handling techniques to enable service robots to precisely understand their users' utterance so that they can provide the reliable services to their users. A novel integrated system to handle lexical vagueness is proposed in this research based on an in-depth understanding of lexical ambiguity and lexical vagueness including why they exist, how they are presented, what differences are in between them, and the mainstream techniques to handle lexical ambiguity and lexical vagueness. The integrated system consists of two blocks: the block of lexical ambiguity handling and the block of lexical vagueness handling. The block of lexical ambiguity handling first removes syntactic ambiguity and lexical ambiguity. The block of lexical vagueness handling is then used to model and remove lexical vagueness. Experimental results show that the robots endowed with the developed integrated system are able to understand their users' utterances. The reliable services to their users, therefore, can be provided by the robots.
Citation:
Guo, X. 'Lexical vagueness handling using fuzzy logic in human robot interaction' PhD thesis. University of Bedfordshire.
Publisher:
University of Bedfordshire
Issue Date:
Oct-2011
URI:
http://hdl.handle.net/10547/294440
Type:
Thesis or dissertation
Language:
en
Description:
Thesis submitted for the degree of Doctor of Philosophy at the University of Bedfordshire.
Appears in Collections:
PhD e-theses

Full metadata record

DC FieldValue Language
dc.contributor.authorGuo, Xiaoen_GB
dc.date.accessioned2013-06-24T10:34:50Z-
dc.date.available2013-06-24T10:34:50Z-
dc.date.issued2011-10-
dc.identifier.citationGuo, X. 'Lexical vagueness handling using fuzzy logic in human robot interaction' PhD thesis. University of Bedfordshire.en_GB
dc.identifier.urihttp://hdl.handle.net/10547/294440-
dc.descriptionThesis submitted for the degree of Doctor of Philosophy at the University of Bedfordshire.en_GB
dc.description.abstractLexical vagueness is a ubiquitous phenomenon in natural language. Most of previous works in natural language processing (NLP) consider lexical ambiguity as the main problem in natural language understanding rather than lexical vagueness. Lexical vagueness is usually considered as a solution rather than a problem in natural language understanding since precise information is usually failed to be provided in conversations. However, lexical vagueness is obviously an obstacle in human robot interaction (HRI) since the robots are expected to precisely understand their users' utterances in order to provide reliable services to their users. This research aims to develop novel lexical vagueness handling techniques to enable service robots to precisely understand their users' utterance so that they can provide the reliable services to their users. A novel integrated system to handle lexical vagueness is proposed in this research based on an in-depth understanding of lexical ambiguity and lexical vagueness including why they exist, how they are presented, what differences are in between them, and the mainstream techniques to handle lexical ambiguity and lexical vagueness. The integrated system consists of two blocks: the block of lexical ambiguity handling and the block of lexical vagueness handling. The block of lexical ambiguity handling first removes syntactic ambiguity and lexical ambiguity. The block of lexical vagueness handling is then used to model and remove lexical vagueness. Experimental results show that the robots endowed with the developed integrated system are able to understand their users' utterances. The reliable services to their users, therefore, can be provided by the robots.en_GB
dc.language.isoenen
dc.publisherUniversity of Bedfordshireen_GB
dc.subjectG710 Speech and Natural Language Processingen_GB
dc.subjectnatural language processingen_GB
dc.subjectfuzzy logicen_GB
dc.subjectlexical vaguenessen_GB
dc.subjecthuman robot interactionen_GB
dc.titleLexical vagueness handling using fuzzy logic in human robot interactionen
dc.typeThesis or dissertationen
dc.type.qualificationnamePhDen_GB
dc.type.qualificationlevelPhDen
dc.publisher.institutionUniversity of Bedfordshireen_GB
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