Validity of jitter measures in non-quasi-periodic voices. Part II: The effect of noise

Abstract In this paper the effect of noise on both perceptual and automatic evaluation of the glottal cycle length in irregular voice signals (sustained vowels) is studied. The reliability of four tools for voice analysis (MDVP, Praat, AMPEX, and BioVoice) is compared to visual inspection made by trained clinicians using two measures of voice signal irregularity: the jitter (J) and the coefficient of variation of the fundamental frequency (F0CV). The purpose is also to test to what extent of irregularity trained raters are capable of determining visually the glottal cycle length as compared to dedicated software tools. For a perfect control of the amount of jitter and noise put in, data consist of synthesized sustained vowels corrupted by increasing jitter and noise. Both jitter and noise can be varied to the desired extent according to built-in functions. All the tools give almost reliable measurements up to 15% of jitter, for low or moderate noise, while only few of them are reliable for higher jitter and noise levels and would thus be suited for perturbation measures in strongly irregular voice signals. As shown in Part I of this work, for low noise levels the results obtained by visual inspection from expert raters are comparable or better than those obtained with the tools presented here, at the expense of a larger amount of time devoted to searching visually for the glottal cycle lengths in the signal waveform. In this paper it is shown that results rapidly deteriorate with increasing noise. Hence, the use of a robust tool for voice analysis can give valid support to clinicians in term of reliability, reproducibility of results, and time-saving.

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

[2]  Jean Schoentgen,et al.  Perceived naturalness of a synthesizer of disordered voices , 2009, INTERSPEECH.

[3]  Jean Schoentgen,et al.  Evaluation of a Synthesizer of Disordered Voices , 2009 .

[4]  Rabab Kreidieh Ward,et al.  Obtaining LIP and Glottal Reflection Coefficients from Vowel Sounds , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[5]  Jean Schoentgen,et al.  Shaping function models of the phonatory excitation signal. , 2003, The Journal of the Acoustical Society of America.

[6]  D G Jamieson,et al.  A comparison of high precision F0 extraction algorithms for sustained vowels. , 1999, Journal of speech, language, and hearing research : JSLHR.

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

[8]  C Manfredi,et al.  A comparative analysis of fundamental frequency estimation methods with application to pathological voices. , 2000, Medical engineering & physics.

[9]  Claudia Manfredi,et al.  A new insight into postsurgical objective voice quality evaluation: application to thyroplastic medialization , 2006, IEEE Transactions on Biomedical Engineering.

[10]  J. Markel,et al.  The SIFT algorithm for fundamental frequency estimation , 1972 .

[11]  Dimitar D. Deliyski,et al.  Acoustic model and evaluation of pathological voice production , 1993, EUROSPEECH.

[12]  平野 実 Clinical examination of voice , 1981 .

[13]  J P Martens,et al.  Pitch and voiced/unvoiced determination with an auditory model. , 1992, The Journal of the Acoustical Society of America.

[14]  John H. L. Hansen,et al.  Discrete-Time Processing of Speech Signals , 1993 .

[15]  Leonardo Bocchi,et al.  A multipurpose user-friendly tool for voice analysis: Application to pathological adult voices , 2009, Biomed. Signal Process. Control..

[16]  P. Boersma ACCURATE SHORT-TERM ANALYSIS OF THE FUNDAMENTAL FREQUENCY AND THE HARMONICS-TO-NOISE RATIO OF A SAMPLED SOUND , 1993 .

[17]  John Nicholas Holmes,et al.  Speech synthesis , 1972 .

[18]  Dimitar D Deliyski,et al.  Influence of sampling rate on accuracy and reliability of acoustic voice analysis , 2005, Logopedics, phoniatrics, vocology.

[19]  J Schoentgen Stochastic models of jitter. , 2001, The Journal of the Acoustical Society of America.