Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech
By: J. Přibil and A. Přibilová
Open Access
|Sep 2009References
- Iriondo, I., et al. (2009). Automatic refinement of an expressive speech corpus assembling subjective perception and automatic classification., 51 (9), 744-758.
- Gobl, C., Ní Chasaide, A. (2003). The role of voice quality in communicating emotion, mood and attitude., 40 (1-2), 189-212.
- d'Alessandro, C., et al. (1998). Effectiveness of a periodic and aperiodic decomposition method for analysis of voice sources., 6, 12-23.
- Schoentgen, J. (2003). Decomposition of vocal cycle length perturbations into vocal jitter and vocal microtremor, and comparison of their size in normophonic speakers., 17, 114-125.
- Shahnaz, C., et al. (2006). A new technique for the estimation of jitter and shimmer of voiced speech signal. In. IEEE, 2112-2115.
- Farrús, M., et al. (2007). Jitter and shimmer measurements for speaker recognition. In. Curran Associates, 778-781.
- Perrot, P., et al. (2007). Voice disguise and automatic detection: review and perspectives. In Stylianou, Y., Faundez-Zanuy, M., Esposito, A. (eds.). Springer, 101-117.
- Murphy, P. (2008). Source-filter comparison of measurements of fundamental frequency perturbation and amplitude perturbation for synthesized voice signals., 22, 125-137.
- Juslin, P.N., Laukka, P. (2003). Communication of emotions in vocal expression and music performance: different channels, same code?, 129, 770-814.
- Tao, J., et al. (2009). Realistic visual speech synthesis based on hybrid concatenation method., 17, 469-477.
- Přibilová, A., Přibil, J. (2006). Non-linear frequency scale mapping for voice conversion in text-to-speech system with cepstral description., 48, 1691-1703.
- Přibilová, A., Přibil, J. (2009). Spectrum modification for emotional speech synthesis. In Esposito, A., Hussain, A., Marinaro, M., Martone, R. (eds.). Springer, 232-241.
- Vích, R. (2000). Cepstral speech model, Padé approximation, excitation, and gain matching in cepstral speech synthesis. In. Brno: University of Technology, 77-82.
- Gray, A.H., Jr., Markel, J.D. (1974). A spectral-flatness measure for studying the autocorrelation method of linear prediction of speech analysis., ASSP-22, 207-217.
- Ito, T., et al. (2005). Analysis and recognition of whispered speech., 45, 139-152.
- Přibil, J., Přibilová, A. (2006). Voicing transition frequency determination for harmonic speech model. In, 25-28.
- Scherer, K.R. (2003). Vocal communication of emotion: a review of research paradigms., 40, 227-256.
- Iida, A., et al. (2003). A corpus-based speech synthesis system with emotion., 40, 161-187.
- Oppenheim, A.V., Schafer, R.W. (1989).. New Jersey: Prentice Hall.
- Suhov, Y., Kelbert, M. (2005).. Cambridge University Press.
- Boersma, P., Weenink, D. (2008).[Computer Program]. Retrieved August 12, 2008, from
- Boersma, P., Weenink, D. (2007).. Retrieved September 5, 2007, from
- Vich, R., Nouza, J., Vondra, M. (2008). Automatic speech recognition used for intelligibility assessment of text-to-speech systems In Esposito, A., et al. (eds.). Springer, 136-148.
DOI: https://doi.org/10.2478/v10048-009-0016-4 | Journal eISSN: 1335-8871
Language: English
Page range: 95 - 104
Published on: Sep 3, 2009
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Related subjects:
© 2009 J. Přibil, A. Přibilová, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons License.