A computer system for acoustic analysis of pathological voices and laryngeal diseases screening

Hadjitodorov, Stefan; Mitev, Petar

doi:10.1016/s1350-4533(02)00031-0

Cited by 105 publications

(57 citation statements)

References 24 publications

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“…An approach found in (Hadjitodorov & Mitev, 2002), where the authors use several parameters and a new parameter called turbulent noise estimation to detect pathological voices , the system reached an accuracy of 96.1% using a k-means nearest neighbor (k-NN).…”

Section: Related Workmentioning

confidence: 99%

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

Saudi¹,

Youssif²,

Ghalwash³

2012

CIS

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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.

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Section: Related Workmentioning

confidence: 99%

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

Saudi¹,

Youssif²,

Ghalwash³

2012

CIS

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“…This research included only 24 patients. Hadjitodorov and Mitev (2002) also report the level of 100% accuracy in the detection for well-manifested voice pathologies, and 96,1% accuracy of weakly manifested pathologies were achieved for the K-nearest neighbours using turbulent noise in voice signals (turbulent noise index, TNI) and for breathy voice characterization (normalized first harmonic energy, NFHE). The database contained 744 patients, of whom 638 suffered from various functional and organic larynx disorders.…”

Section: Introductionmentioning

confidence: 97%

Acoustic analysis assessment in speech pathology detection

Panek

Skalski

Gajda

et al. 2015

International Journal of Applied Mathematics and Computer Science

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Automatic detection of voice pathologies enables non-invasive, low cost and objective assessments of the presence of disorders, as well as accelerating and improving the process of diagnosis and clinical treatment given to patients. In this work, a vector made up of 28 acoustic parameters is evaluated using principal component analysis (PCA), kernel principal component analysis (kPCA) and an auto-associative neural network (NLPCA) in four kinds of pathology detection (hyperfunctional dysphonia, functional dysphonia, laryngitis, vocal cord paralysis) using the a, i and u vowels, spoken at a high, low and normal pitch. The results indicate that the kPCA and NLPCA methods can be considered a step towards pathology detection of the vocal folds. The results show that such an approach provides acceptable results for this purpose, with the best efficiency levels of around 100%. The study brings the most commonly used approaches to speech signal processing together and leads to a comparison of the machine learning methods determining the health status of the patient.

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“…Have obtained 100% accuracy with long-term average spectral properties, glottal noise measures and linear predictive modeling techniques [12]. Obtained 100% accuracy for diagnosed pathologies and 96.1% for ambiguous pathological conditions [13]. Has obtained 89.3% accuracy for Asthenia disease with MFCC, HNR, NNE, GTNE and PCA [14].…”

Section: Introduction Ankışhan H Voice Disorders Detectionmentioning

confidence: 99%

A New Approach for Detection of Pathological Voice Disorders with Reduced Parameters

Ankishan¹

2018

IU-JEEE

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A computer system for acoustic analysis of pathological voices and laryngeal diseases screening

Cited by 105 publications

References 24 publications

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

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

Acoustic analysis assessment in speech pathology detection

A New Approach for Detection of Pathological Voice Disorders with Reduced Parameters

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