A comparison of human and statistical language model performance using missing-word tests.

This paper presents results from a series of missing-word tests, in which a small fragment of text is presented to human subjects who are then asked to suggest a ranked list of completions. The same experiment is repeated with the WA model, an n-gram statistical language model. From the completion d...

Descripción completa

Detalles Bibliográficos
Publicado en:Language & Speech Vol. 40; no. 4; pp. 377 - 390
Autores principales: Owens M, O'Boyle P, McMahon J, Ming J, Smith FJ
Formato: research tables/charts Journal Article
Publicado: Sage Publications Inc. Oct-Dec97
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=107276595&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 107276595
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        00238309
        3YY
      jtl: Language & Speech
      issn: 00238309
      maglogo: Y
    pubinfo:
      dt: Oct-Dec97
      vid: 40
      iid: 4
      pid: 344
      pub: Sage Publications Inc.
      place: Thousand Oaks, California
    artinfo:
      ui:
        107276595
        1998048545
        10.1177/002383099704000404
        107276595
      ppf: 377
      ppct: 13
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: A comparison of human and statistical language model performance using missing-word tests.
      aug:
        au:
          Owens M
          O'Boyle P
          McMahon J
          Ming J
          Smith FJ
        affil: The Queen's University of Belfast. E-mail: m.owens@uk.ac.qub
      sug:
        subj:
          Language Tests
          Language Processing
          Models, Statistical
          Comparative Studies
          Female
          Male
          Adult
          Test Taking
          Grammar
          Chi Square Test
          Descriptive Statistics
          Pearson's Correlation Coefficient
          Human
          Adult: 19-44 years
          Female
          Male
      ab: This paper presents results from a series of missing-word tests, in which a small fragment of text is presented to human subjects who are then asked to suggest a ranked list of completions. The same experiment is repeated with the WA model, an n-gram statistical language model. From the completion data two measures are obtained: (i) verbatim predictability, which indicates the extent to which subjects nominated exactly the missing word and (ii) grammatical class predictability, which indicates the extent to which subjects nominated words of the same grammatical class as the missing word. The differences in language model performance and human performance are encouragingly small, especially for verbatim predictability. This is especially significant given that the WA model was able, on average, to use at most half the available context. The results highlight human superiority in handling missing content words. Most importantly, the experiments illustrate the detailed information one can obtain about the performance of a language model through using missing-word tests.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N