The effectiveness of the glottal to noise excitation ratio for the screening of voice disorders.

This paper evaluates the capabilities of the Glottal to Noise Excitation Ratio for the screening of voice disorders. A lot of effort has been made using this parameter to evaluate voice quality, but there do not exist any studies that evaluate the discrimination capabilities of this acoustic parameter to classify between normal and pathological voices, and neither are there any previous studies that reflect the normative values that could be used for screening purposes. A set of 226 speakers (53 normal and 173 pathological) taken from a voice disorders database were used to evaluate the usefulness of this parameter for discriminating normal and pathological voices. To evaluate this parameter, the effect of the bandwidth of the Hilbert envelopes and the frequency shift have been analyzed, concluding that a good discrimination is obtained with a bandwidth of 1000 Hz and a frequency shift of 300 Hz. The results confirm that the Glottal to Noise Excitation Ratio provides reliable measurements in terms of discrimination among normal and pathological voices, comparable to other classical long-term noise measurements found in the literature, such as Normalized Noise Energy or Harmonics to Noise Ratio, so this parameter can be considered a good choice for screening purposes.

[1]  Pedro Gómez Vilda,et al.  Dimensionality Reduction of a Pathological Voice Quality Assessment System Based on Gaussian Mixture Models and Short-Term Cepstral Parameters , 2006, IEEE Transactions on Biomedical Engineering.

[2]  D. Jamieson,et al.  Acoustic discrimination of pathological voice: sustained vowels versus continuous speech. , 2001, Journal of speech, language, and hearing research : JSLHR.

[3]  J Damborenea Tajada,et al.  [The effect of tobacco consumption on acoustic voice analysis]. , 1999, Acta otorrinolaringologica espanola.

[4]  N Yanagihara,et al.  Significance of harmonic changes and noise components in hoarseness. , 1967, Journal of speech and hearing research.

[5]  B Weinberg,et al.  Minimizing the effect of period determination on the computation of amplitude perturbation in voice. , 1995, The Journal of the Acoustical Society of America.

[6]  E. Yumoto,et al.  Harmonics-to-noise ratio and psychophysical measurement of the degree of hoarseness. , 1984, Journal of speech and hearing research.

[7]  Hans Werner Strube,et al.  Glottal-to-Noise Excitation Ratio - a New Measure for Describing Pathological Voices , 1997 .

[8]  V. Wolfe,et al.  Pathologic voice type and the acoustic prediction of severity. , 1995, Journal of speech and hearing research.

[9]  Ronald J. Baken,et al.  Clinical measurement of speech and voice , 1987 .

[10]  Stefan Todorov Hadjitodorov,et al.  Laryngeal pathology detection by means of class-specific neural maps , 2000, IEEE Transactions on Information Technology in Biomedicine.

[11]  Claudia Manfredi,et al.  Adaptive noise energy estimation in pathological speech signals , 2000, IEEE Transactions on Biomedical Engineering.

[12]  G. de Krom A cepstrum-based technique for determining a harmonics-to-noise ratio in speech signals. , 1993, Journal of speech and hearing research.

[13]  B. Walden,et al.  An evaluation of residue features as correlates of voice disorders. , 1987, Journal of communication disorders.

[14]  H. Kasuya,et al.  Normalized noise energy as an acoustic measure to evaluate pathologic voice. , 1986, The Journal of the Acoustical Society of America.

[15]  J A Preciado,et al.  [Digital analysis of the acoustic signal in vocal pathology diagnosis. Sensitivity and specificity of shimmer and jitter measurements]. , 1998, Acta otorrinolaringologica espanola.

[16]  D Michaelis,et al.  Selection and combination of acoustic features for the description of pathologic voices. , 1998, The Journal of the Acoustical Society of America.

[17]  Tim Ritchings,et al.  Pathological voice quality assesment using artificial neural networks , 2001, MAVEBA.

[18]  Stefan Hadjitodorov,et al.  A computer system for acoustic analysis of pathological voices and laryngeal diseases screening. , 2002, Medical engineering & physics.

[19]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[20]  B Boyanov,et al.  Acoustic analysis of pathological voices. A voice analysis system for the screening of laryngeal diseases. , 1997, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[21]  Guus de Krom,et al.  A Cepstrum-Based Technique for Determining a Harmonics-to-Noise Ratio in Speech Signals , 1993 .

[22]  Y. Qi,et al.  Temporal and spectral estimations of harmonics-to-noise ratio in human voice signals. , 1997, The Journal of the Acoustical Society of America.

[23]  D. Jamieson,et al.  Identification of pathological voices using glottal noise measures. , 2000, Journal of speech, language, and hearing research : JSLHR.

[24]  Alan V. Oppenheim,et al.  Discrete-time signal processing (2nd ed.) , 1999 .

[25]  S. Feijóo,et al.  Short-term stability measures for the evaluation of vocal quality. , 1990, Journal of speech and hearing research.

[26]  F. Klingholz The measurement of the signal-to-noise ratio (SNR) in continuous speech , 1987, Speech Commun..

[27]  T. Baer,et al.  Harmonics-to-noise ratio as an index of the degree of hoarseness. , 1982, The Journal of the Acoustical Society of America.

[28]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[29]  Pedro Gómez-Vilda,et al.  An integrated tool for the diagnosis of voice disorders , 2006 .

[30]  J DamboreneaTajada,et al.  The effect of tobacco consumption on acoustic voice analysis , 1999 .

[31]  J. Hanley,et al.  A method of comparing the areas under receiver operating characteristic curves derived from the same cases. , 1983, Radiology.

[32]  R Fernández Liesa,et al.  Acoustic analysis of the normal voice in nonsmoking adults , 1999 .

[33]  Stefan Hadjitodorov,et al.  ACOUSTIC ANALYSIS OF PATHOLOGICAL VOICES , 1997 .