Computer Aided Recognition of Vocal Folds Disorders by Means of RASTA-PLP

Abstract

In the context of the recognition of vocal folds disorders, the systems based on acoustic analysis are being introduced as computer aided medical diagnosis tools due to its objectivity and noninvasive nature. Acoustic analysis is a complementary tool to those methods based on direct observation of the vocal folds by laryngoscopy; also, it can be used for the evaluation of surgical operation. This paper presents a novel approach in voice pathology assessment using RASTA-PLP feature extraction method in the framework of a HMM. The proposed method then compared to other feature extraction methods such as MFCC and PLP. The experimental results show that RASTA-PLP attained 92.86% correct classification rates and AUC of 0.94 compared to 0.81 and 0.79 for MFCC and PLP respectively.

Automatic Speaker Recognition for Mobile Forensic Applications

“…Other alternative feature representations are studied as an alternative to the MFCCs: perceptual linear prediction (PLP) and relative spectral transform-PLP (RASTA-PLP). The RASTA-PLP is dependent on the PLP acoustic model developed by Hermansky in 1989 [13], in which a band-pass filter is added to the energy in each frequency of PLP [14].…”

Fusing voice and query data for non-invasive detection of laryngeal disorders

“…Voice is a convenient non-invasive modality of information about subject's larynx and audio analysis is being applied increasingly (Godino-Llorente et al, 2001;Dibazar et al, 2002;Hadjitodorov & Mitev, 2002;Godino-Llorente & Vilda, 2004;Alonso et al, 2005;Moran et al, 2006;Sáenz-Lechón et al, 2006;Shama et al, 2007;Sáenz-Lechón et al, 2008;Gelzinis et al, 2008;Salhi et al, 2008;Hariharan et al, 2009;Henriquez et al, 2009;Marinus et al, 2009;Markaki & Stylianou, 2009Martínez et al, 2012;Saudi et al, 2012;Vaiciukynas et al, 2012Vaiciukynas et al, , 2014b. Even telephone-based voice samples (Moran et al, 2006) and compressed recordings (Sáenz-Lechón et al, 2008) may lend itself to voice pathology detection.…”

“…Voice data-based detection of mildly pathological larynx by Vaiciukynas et al (2014a,b) also gave promising results. For overview of the field, refer to Sáenz-Lechón et al (2006); Gelzinis et al (2008); Saudi et al (2012).…”