Acoustic voice quality description: Case studies for different regions of the hoarseness diagram

The hoarseness diagram supplies a method to quantitatively describe the periodicity and the noise content of voices. It is based on four acoustic measures, three of which assess different aspects of periodicity (jitter, shimmer, mean period correlation) while one indicates the relative amount of additive noise (glottal to noise excitation ratio). The behavior of these measures is discussed in detail for four examples of voices found in different regions of the hoarseness diagram. The values obtained are consistent with the theoretical considerations that led to the design of the hoarseness diagram which confirms its reliability. Additionally, the necessity is demonstrated to apply a parabolic interpolation for the waveform matching algorithm that is used to determine the glottal cycle length.

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

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

[3]  D. Klatt,et al.  Analysis, synthesis, and perception of voice quality variations among female and male talkers. , 1990, The Journal of the Acoustical Society of America.

[4]  P. Milenkovic,et al.  Least mean square measures of voice perturbation. , 1987, Journal of speech and hearing research.

[5]  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.

[6]  Y. Koike Application of Some Acoustic Measures for the Evaluation of Laryngeal Dysfunction , 1967 .

[7]  I. Titze,et al.  Comparison of Fo extraction methods for high-precision voice perturbation measurements. , 1993, Journal of speech and hearing research.

[8]  John E. Markel,et al.  Linear Prediction of Speech , 1976, Communication and Cybernetics.

[9]  D J Povel,et al.  Predicting voice quality of deaf speakers on the basis of glottal characteristics. , 1990, Journal of speech and hearing research.

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

[11]  J Kreiman,et al.  Comparison of voice analysis systems for perturbation measurement. , 1993, Journal of speech and hearing research.

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

[13]  M. Hirano,et al.  Acoustic analysis of pathological voice. Some results of clinical application. , 1988, Acta oto-laryngologica.

[14]  J. Hillenbrand,et al.  Perception of aperiodicities in synthetically generated voices. , 1988, The Journal of the Acoustical Society of America.

[15]  C R Rabinov,et al.  Comparing reliability of perceptual ratings of roughness and acoustic measure of jitter. , 1995, Journal of speech and hearing research.