Rubén Fraile

Automatic detection of voice impairments from text-dependent running speech

Abstract Acoustic analysis is a useful tool to diagnose voice diseases. Furthermore it presents several advantages: it is non-invasive, provides an objective diagnostic and, also, it can be used for the evaluation of surgical and pharmacological treatments and rehabilitation processes. Most of the approaches found in the literature address the automatic detection of voice impairments from speech by using the sustained phonation of vowels. In this paper it is proposed a new scheme for the detection of voice impairments from text-dependent running speech. The proposed methodology is based on the segmentation of speech into voiced and non-voiced frames, parameterising each voiced frame with mel-frequency cepstral parameters. The classification is carried out using a discriminative approach based on a multilayer perceptron neural network. The data used to train the system were taken from the voice disorders database distributed by Kay Elemetrics. The material used for training and testing contains the running speech corresponding to the well known “rainbow passage” of 140 patients (23 normal and 117 pathological). The results obtained are compared with those using sustained vowels. The text-dependent running speech showed a light improvement in the accuracy of the detection.

Automatic detection of laryngeal pathologies in records of sustained vowels by means of mel-frequency cepstral coefficient parameters and differentiation of patients by sex.

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.

Mobile radio bi-dimensional large-scale fading modelling with site-to-site cross-correlation

Wireless 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. Copyright

Segmentation of the glottal space from laryngeal images using the watershed transform

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 region merging, while the final decision 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 region of interest with a mouse click. In any case, some a priori knowledge about the glottal space is needed, but this a priori knowledge can be considered weak compared to the environmental conditions fixed in former works.

Pathological Likelihood Index as a Measurement of the Degree of Voice Normality and Perceived Hoarseness

A new index is introduced in this article to measure the degree of normality in the speech. The proposed parameter has demonstrated to be correlated with the perceived hoarseness, giving an indication of the degree of normality. The calculation of such a parameter is based on a statistical model developed to represent normal and pathological voices. The modeling is built around Gaussian mixture models and Mel frequency cepstral coefficients. The proposed index has been named pathological likelihood index (PLI). PLI is compared with other aperiodicity features (such as jitter and shimmer), and measurements sensitive to additive noise (such as harmonics-to-noise ratio (HNR), cepstrum-based HNR, normalized noise energy, and glottal-to-noise excitation ratio). The proposed parameter is revealed to be a good estimator of the presence of pathology, showing lower correlation with noise, frequency, and amplitude perturbation parameters than these classical features among them.

Effect of Shadowing Correlation Modeling on the System Level Performance of Adaptive Radio Resource Management Techniques

The use of software emulators to evaluate complex mobile communication systems is becoming increasingly useful and common. To conduct a valid and accurate study, the models employed in such simulators need to be carefully selected. On the other hand, increasing the complexity of such models in situations in which they do not affect or interact with the particular technique under study only contributes at increasing the simulators implementation and simulation costs. In this context, this work aims at evaluating the impact of considering different types of correlation when developing shadowing models for system level investigations. For that purpose, link adaptation, an adaptive radio resource management technique, has been considered as a case study.

Cepstral peak prominence: A comprehensive analysis

Abstract 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.

Complete Shadowing Modeling and its Effect on System Level Performance Evaluation

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.

Characterization of Dysphonic Voices by Means of a Filterbank-Based Spectral Analysis: Sustained Vowels and Running Speech

OBJECTIVES This article presents a comparative study of the spectral power distribution for normal and dysphonic voices, both for sustained vowels and running speech. The objective of this study was to find robust cues of dysphonia in spectral domain. For this purpose, recordings from two databases are processed, one of them including both sustained vowels and running speech. Additionally, a new measure of stability is introduced (decorrelation time). The application of this measure to the power spectrum is also tested as a cue of dysphonia. MATERIALS AND METHODS The spectral analysis is done having both an auditory model and the filterbank approach as references to the computation of discrete spectrograms. Results are obtained from three sets of recordings belonging to two different databases. RESULTS The reported results indicate that only minor differences exist in the shape of the power spectrum of normal and dysphonic voices when performing sustained vowel phonation tasks. However, the calculated band power decorrelation times indicate that power in bands between 2000 and 6400Hz is significantly less stable in dysphonic voices. As for running speech, the stability of spectral power is not such a good indicator of dysphonia, but there is a significant difference between normal and dysphonic voices in the power level of high-frequency bands (above 5300Hz). In addition, this means that sampling rates above 10.6ksps are needed for assessing running speech in spectral domain. Also, the results involving decorrelation times indicate that for short-time spectral analysis, frame rates above 100 frames/s should be preferred.

Physical simulation of laryngeal disorders using a multiple-mass vocal fold model

Abstract This paper reports on the use of a high-dimensional discrete vocal fold model for the simulation of voice production under the presence of laryngeal disorders. Specifically, the effect of increases in mass and stiffness, both unilateral and bilateral, has been analysed independently for both magnitudes. The glottal flow waveform and the mass displacement have been studied and the obtained results are coherent with clinical observations that relate mass increments with lowered fundamental frequencies and mass and stiffness increments with reduced vibratory amplitudes of vocal folds. The reported results also indicate that asymmetries in the physical properties of vocal folds result in asymmetries in their vibratory patterns, including phase, amplitude and behaviour on collision. These are also correlated with voice perturbation measures such as jitter, shimmer and normalised noise energy.