By Bertrand Rivet, Jonathon Chambers (auth.), Jordi Solé-Casals, Vladimir Zaiats (eds.)
This quantity comprises the complaints of NOLISP 2009, an ISCA educational and Workshop on Non-Linear Speech Processing held on the collage of Vic (- talonia, Spain) in the course of June 25-27, 2009. NOLISP2009wasprecededbythreeeditionsofthisbiannualeventheld2003 in Le Croisic (France), 2005 in Barcelona, and 2007 in Paris. the most notion of NOLISP workshops is to offer and talk about new principles, thoughts and effects concerning substitute techniques in speech processing which could leave from the mainstream. so one can paintings on the front-end of the topic zone, the subsequent domain names of curiosity were de?ned for NOLISP 2009: 1. Non-linear approximation and estimation 2. Non-linear oscillators and predictors three. Higher-order facts four. self sufficient part research five. Nearest acquaintances 6. Neural networks 7. choice bushes eight. Non-parametric versions nine. Dynamics for non-linear platforms 10. Fractal equipment eleven. Chaos modeling 12. Non-linear di?erential equations The initiative to prepare NOLISP 2009 on the college of Vic (UVic) got here from the UVic examine crew on sign Processing and was once supported by way of the Hardware-Software examine staff. we wish to recognize the ?nancial help bought from the M- istry of technology and Innovation of Spain (MICINN), college of Vic, ISCA, and EURASIP. All contributions to this quantity are unique. They have been topic to a doub- blind refereeing approach sooner than their recognition for the workshop and have been revised after being offered at NOLISP 2009.
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Extra resources for Advances in Nonlinear Speech Processing: International Conference on Nonlinear Speech Processing, NOLISP 2009, Vic, Spain, June 25-27. Revised Selected Papers
40 "PRO2" 1 . 130 125 120 . . 40 . 1 . . 40 15 Frames . LDA . 40 600 E[ . ] Fig. 9. Visual features extraction process linear interpolation of the visual features to the audio frame rate is applied. From the up-sampled pictures the Discrete Cosine Transform (DCT) coeﬃcients and proﬁles are extracted. Models and Fusion. The acoustic models are context-independent. Each monophone consists of 3 states, which are modeled by 16 Gaussians each. The HTK Toolkit  software is used for model training and testing.
EGG and DEGG (top panels), acoustic signal (middle panel), and response of the wavelet filterbank (from Vu Ngoc Tuan & d’Alessandro, 2000). For experiments, the speech signal is sampled, and discrete-time signals are analyzed. Then the GCI cannot be determined with accuracy greater than the sampling period, and there is a slight difference between the discrete-time signal maximum and the corresponding continuous-time signal maximum. To increase time-domain accuracy, parabolic interpolation is used.
In: Proc. Voqual 2003. Voice Quality: Functions, analysis and synthesis, ISCA workshop, Geneva, Switzerland, pp. 15–20 (August 2003B) 13. : The spectrum of glottal flow models. Acustica united with Acta Acustica 92, 1026–1046 (2006) 14. : Acoustic theory of speech production, Mouton De Gruyter, Revised edn. (January 1970) 15. : A four-parameter model of glottal flow. STL-QPSR 4, 1–13 (1985) 16. : Glottal characteristics of female speakers: Acoustic correlates. J. Acous. Soc. Am. 101, 466–481 (1997) 17.
Advances in Nonlinear Speech Processing: International Conference on Nonlinear Speech Processing, NOLISP 2009, Vic, Spain, June 25-27. Revised Selected Papers by Bertrand Rivet, Jonathon Chambers (auth.), Jordi Solé-Casals, Vladimir Zaiats (eds.)