245 related articles for article (PubMed ID: 19126465)
1. Effects of audio compression in automatic detection of voice pathologies.
Sáenz-Lechón N; Osma-Ruiz V; Godino-Llorente JI; Blanco-Velasco M; Cruz-Roldán F; Arias-Londoño JD
IEEE Trans Biomed Eng; 2008 Dec; 55(12):2831-5. PubMed ID: 19126465
[TBL] [Abstract][Full Text] [Related]
2. Dimensionality reduction of a pathological voice quality assessment system based on Gaussian mixture models and short-term cepstral parameters.
Godino-Llorente JI; Gómez-Vilda P; Blanco-Velasco M
IEEE Trans Biomed Eng; 2006 Oct; 53(10):1943-53. PubMed ID: 17019858
[TBL] [Abstract][Full Text] [Related]
3. Automatic Voice Pathology Detection With Running Speech by Using Estimation of Auditory Spectrum and Cepstral Coefficients Based on the All-Pole Model.
Ali Z; Elamvazuthi I; Alsulaiman M; Muhammad G
J Voice; 2016 Nov; 30(6):757.e7-757.e19. PubMed ID: 26522263
[TBL] [Abstract][Full Text] [Related]
4. Automatic detection of voice impairments by means of short-term cepstral parameters and neural network based detectors.
Godino-Llorente JI; Gómez-Vilda P
IEEE Trans Biomed Eng; 2004 Feb; 51(2):380-4. PubMed ID: 14765711
[TBL] [Abstract][Full Text] [Related]
5. Telephony-based voice pathology assessment using automated speech analysis.
Moran RJ; Reilly RB; de Chazal P; Lacy PD
IEEE Trans Biomed Eng; 2006 Mar; 53(3):468-77. PubMed ID: 16532773
[TBL] [Abstract][Full Text] [Related]
6. Discrimination between pathological and normal voices using GMM-SVM approach.
Wang X; Zhang J; Yan Y
J Voice; 2011 Jan; 25(1):38-43. PubMed ID: 20137892
[TBL] [Abstract][Full Text] [Related]
7. Multidirectional regression (MDR)-based features for automatic voice disorder detection.
Muhammad G; Mesallam TA; Malki KH; Farahat M; Mahmood A; Alsulaiman M
J Voice; 2012 Nov; 26(6):817.e19-27. PubMed ID: 23177748
[TBL] [Abstract][Full Text] [Related]
8. Validity of jitter measures in non-quasi-periodic voices. Part II: the effect of noise.
Manfredi C; Giordano A; Schoentgen J; Fraj S; Bocchi L; Dejonckere P
Logoped Phoniatr Vocol; 2011 Jul; 36(2):78-89. PubMed ID: 21609247
[TBL] [Abstract][Full Text] [Related]
9. Towards objective evaluation of perceived roughness and breathiness: an approach based on mel-frequency cepstral analysis.
Sáenz-Lechón N; Fraile R; Godino-Llorente JI; Fernández-Baíllo R; Osma-Ruiz V; Gutiérrez-Arriola JM; Arias-Londoño JD
Logoped Phoniatr Vocol; 2011 Jul; 36(2):52-9. PubMed ID: 20849245
[TBL] [Abstract][Full Text] [Related]
10. Automatic detection of pathological voices using complexity measures, noise parameters, and mel-cepstral coefficients.
Arias-Londoño JD; Godino-Llorente JI; Sáenz-Lechón N; Osma-Ruiz V; Castellanos-Domínguez G
IEEE Trans Biomed Eng; 2011 Feb; 58(2):370-9. PubMed ID: 21257362
[TBL] [Abstract][Full Text] [Related]
11. Using modulation spectra for voice pathology detection and classification.
Markaki M; Stylianou Y
Annu Int Conf IEEE Eng Med Biol Soc; 2009; 2009():2514-7. PubMed ID: 19964970
[TBL] [Abstract][Full Text] [Related]
12. On combining information from modulation spectra and mel-frequency cepstral coefficients for automatic detection of pathological voices.
Arias-Londoño JD; Godino-Llorente JI; Markaki M; Stylianou Y
Logoped Phoniatr Vocol; 2011 Jul; 36(2):60-9. PubMed ID: 21073260
[TBL] [Abstract][Full Text] [Related]
13. An Investigation of Multidimensional Voice Program Parameters in Three Different Databases for Voice Pathology Detection and Classification.
Al-Nasheri A; Muhammad G; Alsulaiman M; Ali Z; Mesallam TA; Farahat M; Malki KH; Bencherif MA
J Voice; 2017 Jan; 31(1):113.e9-113.e18. PubMed ID: 27105857
[TBL] [Abstract][Full Text] [Related]
14. Discrimination of pathological voices using a time-frequency approach.
Umapathy K; Krishnan S; Parsa V; Jamieson DG
IEEE Trans Biomed Eng; 2005 Mar; 52(3):421-30. PubMed ID: 15759572
[TBL] [Abstract][Full Text] [Related]
15. Automatic assessment of voice quality according to the GRBAS scale.
Sáenz-Lechón N; Godino-Llorente JI; Osma-Ruiz V; Blanco-Velasco M; Cruz-Roldán F
Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():2478-81. PubMed ID: 17946516
[TBL] [Abstract][Full Text] [Related]
16. Investigation of Voice Pathology Detection and Classification on Different Frequency Regions Using Correlation Functions.
Al-Nasheri A; Muhammad G; Alsulaiman M; Ali Z
J Voice; 2017 Jan; 31(1):3-15. PubMed ID: 26992554
[TBL] [Abstract][Full Text] [Related]
17. Pattern recognition methods applied to respiratory sounds classification into normal and wheeze classes.
Bahoura M
Comput Biol Med; 2009 Sep; 39(9):824-43. PubMed ID: 19631934
[TBL] [Abstract][Full Text] [Related]
18. Acoustic analysis and detection of hypernasality using a group delay function.
Vijayalakshmi P; Reddy MR; O'Shaughnessy D
IEEE Trans Biomed Eng; 2007 Apr; 54(4):621-9. PubMed ID: 17405369
[TBL] [Abstract][Full Text] [Related]
19. Towards noninvasive screening for malignant tumours in human larynx.
Verikas A; Gelzinis A; Bacauskiene M; Uloza V
Med Eng Phys; 2010 Jan; 32(1):83-9. PubMed ID: 19926327
[TBL] [Abstract][Full Text] [Related]
20. [Detection of latent velopharyngeal hyperfunction with the Lombard trial].
Höfler H
Laryngol Rhinol Otol (Stuttg); 1984 Nov; 63(11):596-9. PubMed ID: 6521590
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
