Recognising Groups among Dialects.

In this paper we apply various clustering algorithms to the dialect pronunciation data. At the same time we propose several evaluation techniques that should be used in order to deal with the instability of the clustering techniques. The results have shown that three hierarchical clustering algorith...

Descripción completa

Detalles Bibliográficos
Publicado en:International Journal of Humanities & Arts Computing: A Journal of Digital Humanities Vol. 2; no. 1-2; pp. 153 - 173
Autores principales: Proki, Jelena, Nerbonne, John
Formato: Artículo
Publicado: Edinburgh University Press Mar2008
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=44213963&site=ehost-live
header:
  @attributes:
    shortDbName: hlh
    uiTerm: 44213963
    longDbName: Humanities International Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        17538548
        2QD7
      jtl: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities
      issn: 17538548
      maglogo: N
    pubinfo:
      dt: Mar2008
      vid: 2
      iid: 1-2
      pid: 2327
      pub: Edinburgh University Press
    artinfo:
      ui:
        44213963
        10.3366/E1753854809000366
      ppf: 153
      ppct: 20
      formats:
        fmt:
          @attributes:
            type: P
            size: 1.6MB
      tig:
        atl: Recognising Groups among Dialects.
      aug:
        au:
          Proki, Jelena
          Nerbonne, John
      su:
        Dialects
        Pronunciation
        Linguistic analysis
        Linguistic geography
        Comparative linguistics
        Algorithm research
        Hierarchy (Linguistics)
      sug:
        subj:
          Dialects
          Pronunciation
          Linguistic analysis
          Linguistic geography
          Comparative linguistics
          Algorithm research
          Hierarchy (Linguistics)
      ab: In this paper we apply various clustering algorithms to the dialect pronunciation data. At the same time we propose several evaluation techniques that should be used in order to deal with the instability of the clustering techniques. The results have shown that three hierarchical clustering algorithms are not suitable for the data we are working with. The rest of the tested algorithms have successfully detected two-way split of the data into the Eastern and Western dialects. At the aggregate level that we used in this research, no further division of sites can be asserted with high confidence.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: Y
      custom: Copyright of International Journal of Humanities & Arts Computing: A Journal of Digital Humanities is the property of Edinburgh University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use.
      item: International Journal of Humanities & Arts Computing: A Journal of Digital Humanities
      holder: Edinburgh University Press
      dt:
        @attributes:
          year: 2008
    holdings:
      @attributes:
        islocal: N