Detection of vocal fold paralysis and oedema using time-domain features and Probabilistic Neural Network

International Journal of Biomedical Engineering and Technology

Volumn 6, Issue 1, 2011, Pages 46-57

  Hariharan, M ^a   Paulraj, M P ^a   Yaacob, Sazali ^a  

^a UNIVERSITY MALAYSIA PERLIS   (Malaysia)

Author keywords

Acoustic analysis; PNN; Probabilistic Neural Network; Time domain energy features; Vocal fold paralysis and edema; Vocal fold pathology

Indexed keywords

BIOMEDICAL SIGNAL PROCESSING; FEATURE EXTRACTION; NEURAL NETWORKS; PATHOLOGY; SPEECH;

ACOUSTIC ANALYSIS; CLASSIFICATION ACCURACY; ENERGY FEATURE; FEATURE EXTRACTION METHODS; PATHOLOGICAL SPEECH; PROBABILISTIC NEURAL NETWORKS; TIME DOMAIN FEATURES; VOCAL FOLDS;

TIME DOMAIN ANALYSIS;

EID: 79959277009     PISSN: 17526418     EISSN: 17526426     Source Type: Journal    
DOI: 10.1504/IJBET.2011.040452     Document Type: Article

References (28)

1. Boyanov, B. and Hadjitodorov, S. (1997) 'Acoustic analysis of pathological voices: a voice analysis system for the screening of laryngeal diseases', IEEE Engineering in Medicine and Biology Magazine, Vol. 16, No. 4, pp. 74-82. (Pubitemid 27318793)
2. Boyanov, B. and Ivanov Tm Cholet, G. (1980) 'Robust hybrid pitch detector', Electronics Letters, Vol. 29, pp. 1924-1926.
3. Childers, D. G. and Bae, K. S. (1992) 'Detection of laryngeal function using speech and electroglottograph data', IEEE Transactions on Biomedical Engineering, Vol. 39, pp. 19-25.
4. DeKrom, G. (1993) 'A cepstrum based technique for determining a harmonics to noise ratio in speech signals', Journal of Speech and Hearing Research, Vol. 36, pp. 254-266. (Pubitemid 23123559)
5. Dimital, D. D. (1993) 'Acoustic model and evaluation of pathological voice production', Paper Presented at the 3rd International Conference on Speech Communication and Technology, 22-25 September, Berlin, Germany.
6. Fausett, L. (1994) Fundamentals of Neural Network, Prentice Hall, New Jersey, USA.
7. Feijoo, S. and Hernandez, C. (1990) 'Short-tem stability measures for the evaluation of voice quality', Journal of Speech and Hearing Research, Vol. 33, pp. 324-334. (Pubitemid 20200326)
8. Gelzinis, A., Verikas, A. and Bacauskiene, M. (2008) 'Automated speech analysis applied to laryngeal disease categorization', Computer Methods and Programs in Biomedicine, Vol. 91, No. 1, pp. 36-47.
9. Godino Llorente, J. I. and Gomez-Vilda, P. (2004) 'Automatic detection of voice impairments by means of short-term cepstral parameters and neural network based detectors', IEEE Transactions on Biomedical Engineering, Vol. 51, No. 2, pp. 380-384. (Pubitemid 38133618)
10. Godino Llorente, J. I., Gomez-Vilda, P. and Blanco-Velasco, M. (2006) 'Dimensionality reduction of a pathological voice quality assessment system based on Gaussian mixture models and short-term cepstral parameters', IEEE Transactions on Biomedical Engineering, Vol. 53, pp. 1943-1953. (Pubitemid 44526241)
11. Hernandez-Espinosa, C., Fernandez-Redondo, M., Aguilera-Navarro, S., Gomez-Vilda, P., Godino-Llorente, J. I. and Gomez-Vilda, P. (2000) 'Diagnosis of vocal and voice disorders by the speech signal', Paper Presented at the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 24-27 July, Como, Italy.
12. Kasuya, H. E. and Sliu, S. (1993) 'Novel acoustic measurements of jitter and shimmer characteristics from pathological voice', Paper Presented at the 3rd International Conference on Speech Communication and Technology, 22-25 September, Berlin, Germany.
13. Kausya, H., Ogawa, S. and Mashima, K. (1986) 'Normalized noise energy as an acoustic measure to evaluate pathologic voice', Journal of the Acoustical Society of America, Vol. 80, pp. 1329-1334. (Pubitemid 17183478)
14. Kohavi, R. (1995) 'A study of cross validation and bootstrap for accuracy estimation and model selection', Paper Presented at the 14th International Conference on Artificial Intelligence, 20-25 August, Montreal, Quebec, Canada.
15. Ludlow, C., Bassich, C., Connor, N., Coulter, D. and Lee, Y. (1987) 'The validity of using phonatory jitter and shimmer to detect laryngeal pathology', Laryngeal Function in Phonation and Respiration, Brown & Co., Boston, USA, pp. 492-508.
16. Martinez Cesar, E. and Rufiner Hugo, L. (2000) 'Acoustic analysis of speech for detection of laryngeal pathologies', Paper Presented at the 22nd Annual IEEE International Conference on Engineering in Medicine and Biology Society, 23-28 July. Chicago IL, USA.
17. Nayak, J., Bhat, P., Acharya, R. and Aithal, U. (2005) 'Classification and analysis of speech abnormalities', ITBM-RBM, Vol. 26, Nos. 5-6, pp. 319-327. (Pubitemid 41787605)
18. Oliveira, R. M., Pereira, J. C. and Grellet, M. (2000) 'Adaptive estimation of residue signal for voice pathology diagnosis', IEEE Transactions in Biomedical Engineering, Vol. 47, No. 1, pp. 96-104. (Pubitemid 30044005)
19. Ritchings, T., McGillion, M. and Moore, C. (2002) 'Pathological voice quality assessment using artificial neural networks', Medical Engineering and Physics, Vol. 24, No. 8, pp. 561-564. (Pubitemid 35266697)
20. Ritchings, T., McGillion, M. A., Moore, C. J. and Conroy, G. V. (1999) 'Objective assessment of pathological voice quality', Paper Presented at the IEEE International Conference on Systems, Man, and Cybernetics, 13-16 October, Atlanta, GA, USA.
21. Shama, K., Krishna, A. and Cholayya, N. U. (2007) 'Study of harmonics-to-noise ratio and critical band energy spectrum of speech as acoustic indicators of laryngeal and voice pathology', EURASIP Journal on Advances in Signal Processing, Hindawi Publishing Corporation, Vol. 2007, No. 1, pp. 1-9.
22. Sivanandam, S. N. and Paulraj, M. (2003) An Introduction to Artificial Neural Networks, Vikhas Publication, India.
23. Specht, D. F. (1990) 'Probabilistic neural networks', Neural Networks, Vol. 3, No. 1, pp. 109-118.
24. Umapathi, K., Krishnan, S., Parsa, V. and Jamieson, D. G. (2005) 'Discrimination of pathological voices using a time-frequency approach', IEEE Transactions on Biomedical Engineering, Vol. 52, No. 3, pp. 421-430. (Pubitemid 40343739)
25. Voice Disorders Database (1994) Massachusetts Eye and Ear Infirmary, 'Voice Disorders Database', Version 1.03 (CDROM), Kay Elemetrics Corporation, Lincoln Park, NJ, USA.
26. Wester, M. (1998) 'Automatic classification of voice quality: comparing regression models and hidden Markov models', Paper Presented at the Symposium on Databases in Voice Quality Research and Education (Proceedings of VOICEDATA98), 28-29 January, Utrecht, Netherlands.
27. Yumoto, E. and Gould, W. J. (1990) 'Harmonics to noise ratio as an index of the degree of hoarseness', Journal of the Acoustical Society of America, Vol. 87, No. 3, pp. 1278-1289.
28. Yunik, M. and Boyanov, B. (1990) 'Method for evaluation of the noise-to harmonic-component ratios in pathological and normal voices', Acoustica, Vol. 70, pp. 89-91.