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1. M. Pannbacker, “ Classification systems of voice disorders: A review of the literature,” Language Speech Hearing Serv. Schools 15, 169174 (1984).
2. M. Hirano, “ Psycho-acoustic evaluation of voice,” in Clinical Examination of Voice (Springer-Verlag, New York, 1981), p. 81.
3. G. de Krom, “ Some spectral correlates of pathological breathy and rough voice quality for different types of vowel fragments,” J. Speech Hear. Res. 38, 794811 (1995).
4. M. A. Toner, F. W. Emanuel, and D. Parker, “ Relationship of spectral noise levels to psychophysical scaling of vowel roughness,” J. Speech Hear. Res. 33(2), 238244 (1990).
5. N. A. MacMillan and C. D. Creelman, Detection Theory: A User's Guide (Psychology Press, New York, 2005).
6. S. A. Patel, R. Shrivastav, and D. A. Eddins, “ Perceptual distances of breathy voice quality: A comparison of psychophysical methods,” J. Voice 24, 168177 (2011).
7. J. Kreiman, B. Gerratt, and M. Ito, “ When and why listeners disagree in voice quality assessment tasks,” J. Acoust. Soc. Am. 122, 23542364 (2007).
8. S. A. Patel, R. Shrivastav, and D. A. Eddins, “ Identifying a comparison for matching roughness.J. Speech Lang. Hear. Res. 55, 14071422 (2012).
9. B. R. Gerratt and J. Kreiman, “ Measuring voice quality with speech synthesis.J. Acoust. Soc. Am. 110, 25602566 (2001).
10. J. Kreiman, N. Antoñanzas-Barroso, and B. R. Gerratt, “ Integrated software for analysis and synthesis of voice quality,” Behav. Res. Methods. 42(4), 10301041 (2010).
11. S. A. Patel, R. Shrivastav, and D. A. Eddins, “ Developing a single reference signal for matching breathy voice quality,” J. Speech Lang. Hear. Res. 55, 639647 (2012).
12. K. Belkin, R. Martin, S. E. Kemp, and A. N. Gilbert, “ Auditory pitch as a perceptual analogue to odor quality,” Psychol Sci. 8, 340342 (1997).
13. J. C. Stevens and J. W. Hall, “ Brightness and loudness as functions of stimulus duration,” Percept. Psychophys. 1, 319327 (1966).
14. W. M. Hartmann and J. Pumplin, “ Periodic signals with minimal power fluctuations,” J. Acoust. Soc. Am. 90, 19861999 (1991).
15. ANSI S3.21-2010: Methods for manual pure-tone threshold audiometry (American National Standards Institute, New York, 2010).

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A psychophysical matching paradigm has been used to better quantify voice quality under laboratory conditions. The goals of this study were to establish which of two candidate comparison stimuli would best ensure that the range of perceived vocal roughness could be adequately bracketed using a matching task and to provide a general solution to the problem of estimating vocal roughness. Psychometric functions for roughness matching indicated that a speech-like sawtooth-plus-noise complex (20 dB signal-to-noise ratio) amplitude modulated by a sinusoidal function raised to the 4th power yielded a comparison stimulus with a perceptual dynamic range well suited for roughness matching.


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