G. Peretti

Bio: G. Peretti is an academic researcher. The author has contributed to research in topics: Voice analysis & Voice Handicap Index. The author has an hindex of 1, co-authored 1 publications receiving 25 citations.

A new insight into postsurgical objective voice quality evaluation: application to thyroplastic medialization

Abstract: This paper aims at providing new objective parameters and plots, easily understandable and usable by clinicians and logopaedicians, in order to assess voice quality recovering after vocal fold surgery. The proposed software tool performs presurgical and postsurgical comparison of main voice characteristics (fundamental frequency, noise, formants) by means of robust analysis tools, specifically devoted to deal with highly degraded speech signals as those under study. Specifically, we address the problem of quantifying voice quality, before and after medialization thyroplasty, for patients affected by glottis incompetence. Functional evaluation after thyroplastic medialization is commonly based on several approaches: videolaryngostroboscopy (VLS), for morphological aspects evaluation, GRBAS scale and Voice Handicap Index (VHI), relative to perceptive and subjective voice analysis respectively, and Multi-Dimensional Voice Program (MDVP), that provides objective acoustic parameters. While GRBAS has the drawback to entirely rely on perceptive evaluation of trained professionals, MDVP often fails in performing analysis of highly degraded signals, thus preventing from presurgical/postsurgical comparison in such cases. On the contrary, the new tool, being capable to deal with severely corrupted signals, always allows a complete objective analysis. The new parameters are compared to scores obtained with the GRBAS scale and to some MDVP parameters, suitably modified, showing good correlation with them. Hence, the new tool could successfully replace or integrate existing ones. With the proposed approach, deeper insight into voice recovering and its possible changes after surgery can thus be obtained and easily evaluated by the clinician.

Model based processing of signals : a state space approach. Prolog

Abstract: This paper is a tutorial on linear, state space, model-based methods for certain nonlinear estimation problems commonly encountered in signal and data analysis. A prototypical problem that is studied is that of estimating the frequencies of multiple, superimposed sinusoids from a short record of noise-corrupted data. The approach expounded however, is applicable to a vast range of nonlinear signal analysis problems and applications in direction finding and damped sinusoid retrieval are dealt with in some detail. The benefits that result from using a state space description of the signal are highlighted in this paper. It is shown that state space models provide an elegant tool for exposing the structure present in the problem. The approach also allows for robust parameterization of the model with respect to finite precision errors. The robustness of the parameter set is complemented by the availability of numerically robust tools to estimate the parameters. The resulting algorithms are compatible with multiprocessor implementations. >

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 an...