Hierarchical Classification and System Combination for Automatically Identifying Physiological and Neuromuscular Laryngeal Pathologies.
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Isabel Guimarães | Hugo Cordeiro | José Fonseca | Carlos Meneses | C. Meneses | José Fonseca | I. Guimarães | Hugo Cordeiro
[1] Kumara Shama,et al. Study of Harmonics-to-Noise Ratio and Critical-Band Energy Spectrum of Speech as Acoustic Indicators of Laryngeal and Voice Pathology , 2007, EURASIP J. Adv. Signal Process..
[2] José R. Fonseca,et al. Spectral envelope and periodic component in classification trees for pathological voice diagnostic , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[3] Carlos Dias Maciel,et al. Relative entropy measures applied to healthy and pathological voice characterization , 2009, Appl. Math. Comput..
[4] Shrikanth Narayanan,et al. Feature analysis for automatic detection of pathological speech , 2002, Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology.
[5] Maurílio N Vieira,et al. On the influence of laryngeal pathologies on acoustic and electroglottographic jitter measures. , 2002, The Journal of the Acoustical Society of America.
[6] Juan Ignacio Godino-Llorente,et al. Automatic Detection of Laryngeal Pathologies in Records of Sustained Vowels by Means of Mel-Frequency Cepstral Coefficient Parameters and Differentiation of Patients by Sex , 2009, Folia Phoniatrica et Logopaedica.
[7] Aaron E. Rosenberg,et al. An improved endpoint detector for isolated word recognition , 1981 .
[8] Luís C. Oliveira,et al. Jitter Estimation Algorithms for Detection of Pathological Voices , 2009, EURASIP J. Adv. Signal Process..
[9] Douglas A. Reynolds,et al. Speaker recognition using G.729 speech codec parameters , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).
[10] D. Jamieson,et al. Acoustic discrimination of pathological voice: sustained vowels versus continuous speech. , 2001, Journal of speech, language, and hearing research : JSLHR.
[11] J.C. Pereira,et al. Normal versus pathological voice signals , 2009, IEEE Engineering in Medicine and Biology Magazine.
[12] Pedro Gómez Vilda,et al. Methodological issues in the development of automatic systems for voice pathology detection , 2006, Biomed. Signal Process. Control..
[13] Hugo Cordeiro,et al. Continuous Speech Classification Systems for Voice Pathologies Identification , 2015, DoCEIS.
[14] C. M. Ribeiro,et al. Speaker adaptation in a phonetic vocoding environment , 1999, 1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351).
[15] Chih-Jen Lin,et al. Errata to "A comparison of methods for multiclass support vector machines" , 2002, IEEE Trans. Neural Networks.
[16] Hugo Cordeiro,et al. Voice pathologies identification speech signals, features and classifiers evaluation , 2015, 2015 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA).
[17] Yannis Stylianou,et al. On combining information from modulation spectra and mel-frequency cepstral coefficients for automatic detection of pathological voices , 2011, Logopedics, phoniatrics, vocology.
[18] Ji Yeoun Lee. A two-stage approach using Gaussian mixture models and higher-order statistics for a classification of normal and pathological voices , 2012, EURASIP J. Adv. Signal Process..
[19] Ron Kohavi,et al. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection , 1995, IJCAI.
[20] Ghulam Muhammad,et al. Automatic Voice Pathology Detection With Running Speech by Using Estimation of Auditory Spectrum and Cepstral Coefficients Based on the All-Pole Model. , 2016, Journal of voice : official journal of the Voice Foundation.
[21] Yannis Stylianou,et al. Voice Pathology Detection and Discrimination Based on Modulation Spectral Features , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[22] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[23] S. Iwata,et al. Periodicities of pitch perturbations in normal and pathologic larynges , 1972, The Laryngoscope.
[24] P. Lieberman. Some Acoustic Measures of the Fundamental Periodicity of Normal and Pathologic Larynges , 1963 .
[25] Hugo Cordeiro,et al. Speaker Characterization with MLSFs , 2006, 2006 IEEE Odyssey - The Speaker and Language Recognition Workshop.
[26] R. Kirschen,et al. The Royal London Space Planning: an integration of space analysis and treatment planning: Part I: Assessing the space required to meet treatment objectives. , 2000, American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics.
[27] Muhammad Ghulam,et al. Automatic voice disorder classification using vowel formants , 2011, 2011 IEEE International Conference on Multimedia and Expo.
[28] Vahid Majidnezhad. A novel hybrid of genetic algorithm and ANN for developing a high efficient method for vocal fold pathology diagnosis , 2015, EURASIP J. Audio Speech Music. Process..
[29] Hong-Goo Kang,et al. An Investigation of Vocal Tract Characteristics for Acoustic Discrimination of Pathological Voices , 2013, BioMed research international.
[30] I. Titze. Orkshop on Acoustic Voice Analysis Summary Statement Vv 2 Workshop on Acoustic Voice Analysis , 2022 .
[31] Yu Zhang,et al. Objective Acoustic Analysis of Pathological Voices from Patients with Vocal Nodules and Polyps , 2009, Folia Phoniatrica et Logopaedica.