An analytical study of cepstral peak prominence (CPP) is presented, intended to provide an insight into its meaning and relation with voice perturbation parameters. To carry out this analysis, a parametric approach is adopted in which voice production is modelled using the traditional source-filter model and the first cepstral peak is assumed to have Gaussian shape. It is concluded that the meaning of CPP is very similar to that of the first rahmonic and some insights are provided on its dependence with fundamental frequency and vocal tract resonances. It is further shown that CPP integrates measures of voice waveform and periodicity perturbations, be them either amplitude, frequency or noise.

SUMMARYWireless communication simulations are generally conducted using one-dimensional models for large-scale fading. While simple and with low computational costs, these models cannot produce correlated fading values for mobiles that are in nearby positions. To overcome this limitation, this paper presents a novel bi-dimensional large-scale fading model which introduces the spatial correlation present in real systems. Besides, it is also able to model the non-negligible cross-correlation among signals coming from different sites.

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Mel-frequency cepstral coefficients (MFCC) have traditionally been used in speaker identification applications. Their use has been extended to speech quality assessment for clinical applications during the last few years. While the significance of such parameters for such an application may not seem clear at first thought, previous research has demonstrated their robustness and statistical significance and, at the same time, their close relationship with glottal noise measurements. This paper includes a review of this parameterization scheme and it analyzes its performance for voice analysis when patients are differentiated by sex. While it is of common use for establishing normative values for traditional voice descriptors (e.g. pitch, jitter, formants), differentiation by sex had not been tested yet for cepstral analysis of voice with clinical purposes. This paper shows that the automatic detection of laryngeal pathology on voice records based on MFCC can significantly improve its performance by means of this prior differentiation by sex.

The present work describes a new method for the automatic detection of the glottal space from laryngeal images obtained either with high speed or with conventional video cameras attached to a laryngoscope. The detection is based on the combination of several relevant techniques in the field of digital image processing. The image is segmented with a watershed transform followed by a región merging, while the final decisión is taken using a simple linear predictor. This scheme has successfully segmented the glottal space in all the test images used.The method presented can be considered a generalist approach for the segmentation of the glottal space because, in contrast with other methods found in literature, this approach does not need either initialization or finding strict environmental conditions extracted from the images to be processed. Therefore, the main advantage is that the user does not have to outline the región of interest with a mouse click. In any case, some a priori knowledge about the glottal space is needed, but this a priorí knowledge can be considered weak compared to the environmental conditions fixed in former works.

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Computer simulations are a common procedure for assessing the performance of new algorithms. To conduct a valid and accurate study, the models employed in such simulators need to be carefully selected. Regarding shadowing modeling, one-dimensional models are fairly commonplace in the literature. While simple and with low computational costs, these models can not produce correlated fading values for mobiles that are in nearby positions and, besides, do not include the cross-correlation effect. To overcome these limitations, this paper presents a bi-dimensional shadowing model which introduces both the spatial correlation and the cross-correlation present in real systems. Finally, the impact of considering different aspects of shadowing modeling for system level investigations is evaluated. For that purpose, the UMTS radio access technology has been considered as a case study.