## 9 Experimental Assessment and Analysis
### Experiment 4: Some Examples Produced for the Italian Language  
In this Section, some experimental analysis of the Italian word _/nove/_ (nine) are reported as an example. The analysis is performed with the fuzzy-genetic algorithm with the following parameters: population size of 200 elements; mutation rate equal to 0.02. Several algorithms for computing the parameters of the Klatt synthetizer have been proposed in the past. Many of them are presented as solutions to the 'copy synthesis' problem, which is the problem to estimate the input parameters to reconstruct a speech signal using a speech synthesizer Copy synthesis is a difficult inverse problem because the mapping is non-linear and often is a 'from many to one' problem. One of them is that proposed by [PERSON] [75], who proposed an iterative algorithm for the automatic estimation of the factors for the Klatt model using the corpus of an annotated audio record of the speaker. Another is that proposed by [PERSON], [76], who describe an approach to track formant trajectories first, and to compute the amplitudes of the resonators by an algorithm derived from cepstral smoothing they called \"true envelope\".  
In Reference [77], a framework for automatically extracting the input parameters of a class of formant-based synthesizers is described. The framework is based on a genetic algorithm. Also [PERSON] et al., in Reference [78], describe a system based on GA optimization for automatically computing the  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline  & **QUA** & **TON** & **APE** & **ANT** & **SON** & **BIL** & **LAB** & **ALV** & **PRE** & **PAL** & **VIB** & **D-V** & **DEN** & **VEL** \\ \hline initial & 0.50 & 0.40 & 0.45 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline [-a] & 0.178 & 0.990 & 0.022 & 1.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 \\ \hline [at] & 0.000 & 0.000 & 0.000 & 0.910 & 0.000 & 0.000 & 0.971 & 0.009 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 \\ \hline [t]a & 0.276 & 0.855 & 0.098 & 1.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 & 0.000 \\ \hline [a-] & 0.50 & 0.40 & 0.45 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline \hline \end{tabular}
\end{table}
Table 6: Estimated articulatory parameters per transition.  
Figure 17: Synthetic speech: /atfa/.  
parameters for the Klatt synthesizer. In Reference [79] it is presented _KlattWork_ which relies on the 1980 version of the Klatt synthesizer. Rather than a copy synthesis system, KlattWorks is a \"manager\", and is designed to allow the user to rapidly develop new synthetic speech for experiments using existing tools.  
[PERSON] developed a class called KlattGrid, which implements a Klatt-type synthesizer. Parameters are automatically computed with the standard speech signal processing routines prodvided by the Praat program [80]. For simplicity,the algorithm KlattGrid provided by Praat for computing the Klatt synthesis system has been used for comparison with the \(Fuzzy-Genetic\) algorithm,  
In Figure 18 we report the trajectories of the first three formant frequencies and of the \(AF\) and \(AV\) amplitudes obtained with the algorithm from the word _move_ (nine) in upper and lower panels respectively. The centers of the three phonemes of the word, that is /n/,/o/,/v/,/e/, are indicated by the three vertical lines.  
In Figure 19 the dynamic of the membership degrees of the articulatory places of articulation is reported.  
Figure 19: Articulatory places of articulation of the Italian word “move”.  
Figure 18: Acoustic analysis of the Italian word “move”.  
Some subjective evaluation results of a phonetic listening test are reported in Table 7. In this test, subjects must identify the phonetic category they perceive. It comes out that the phonetic categories are quite well perceived.