Journal of Voice
Volume 24, Issue 6 , Pages 667-677, November 2010

Pathological Likelihood Index as a Measurement of the Degree of Voice Normality and Perceived Hoarseness

  • Juan Ignacio Godino-Llorente

      Affiliations

    • Universidad Politécnica de Madrid, Circuits & Systems Engineering Department, Ctra. de Valencia, Madrid, Spain
    • Corresponding Author InformationAddress correspondence and reprint requests to Juan Ignacio Godino-Llorente, Universidad Politécnica de Madrid, Ctra. de Valencia, km. 7, 28031, Madrid, Spain.
  • ,
  • Pedro Gómez-Vilda

      Affiliations

    • Universidad Politécnica de Madrid, Circuits & Systems Engineering Department, Ctra. de Valencia, Madrid, Spain
  • ,
  • Fernando Cruz-Roldán

      Affiliations

    • Universidad de Alcalá, Escuela Politécnica, Signal Theory and Communications Department, Ctra. de Madrid-Barcelona, Alcalá de Henares, Madrid, Spain
  • ,
  • Manuel Blanco-Velasco

      Affiliations

    • Universidad de Alcalá, Escuela Politécnica, Signal Theory and Communications Department, Ctra. de Madrid-Barcelona, Alcalá de Henares, Madrid, Spain
  • ,
  • Rubén Fraile

      Affiliations

    • Universidad Politécnica de Madrid, Circuits & Systems Engineering Department, Ctra. de Valencia, Madrid, Spain

Accepted 20 April 2009. published online 08 March 2010.

Summary 

A new index is introduced in this article to measure the degree of normality in the speech. The proposed parameter has demonstrated to be correlated with the perceived hoarseness, giving an indication of the degree of normality. The calculation of such a parameter is based on a statistical model developed to represent normal and pathological voices. The modeling is built around Gaussian mixture models and Mel frequency cepstral coefficients. The proposed index has been named pathological likelihood index (PLI). PLI is compared with other aperiodicity features (such as jitter and shimmer), and measurements sensitive to additive noise (such as harmonics-to-noise ratio (HNR), cepstrum-based HNR, normalized noise energy, and glottal-to-noise excitation ratio). The proposed parameter is revealed to be a good estimator of the presence of pathology, showing lower correlation with noise, frequency, and amplitude perturbation parameters than these classical features among them.

Key Words: Screening voice disorders, Short-term analysis, Cepstral parameters, Gaussian mixture models, Voice quality

To access this article, please choose from the options below

Login to an existing account or Register a new account.

  • Purchase this article for 31.50 USD (You must login/register to purchase this article)

    Online access for 24 hours. The PDF version can be downloaded as your permanent record.

  • Subscribe to this title

    Get unlimited online access to this article and all other articles in this title 24/7 for one year.

  • Claim access now

    For current subscribers with Society Membership or Account Number.

  • Visit SciVerse ScienceDirect to see if you have access via your institution.
 

PII: S0892-1997(09)00056-3

doi:10.1016/j.jvoice.2009.04.003

Journal of Voice
Volume 24, Issue 6 , Pages 667-677, November 2010