Jean Schoentgen

Stochastic models of jitter

This study presents stochastic models of jitter. Jitter designates small, random, involuntary perturbations of the glottal cycle lengths. Jitter is a base-line phenomenon that may be observed in all voiced speech sounds. Knowledge of its properties is therefore relevant to the acoustic modeling, analysis, and synthesis of voice quality. Also, models of jitter are conceptual frameworks that enable experimenters and clinicians to distinguish jitter in particular from aperiodic cycle length patterns in general. Vocal jitter is modeled by means of the ribbon model of the glottal vibration combined with stochastic models of the disturbances of the instantaneous frequency. The disturbance model comprises correlation-free noise and vocal microtremor. Properties of jitter that are simulated are the stochasticity, stationarity, and normality of the decorrelated cycle length perturbations, the size of decorrelated jitter, the correlation between the perturbations of neighboring glottal cycles, the modulation level and modulation frequency owing to microtremor, the asynchrony between external disturbances and glottal cycles, the dependence of the size of jitter on the average glottal cycle length, and the relation between jitter and laryngeal pathologies. Modeled jitter is discussed in the light of measured jitter, as well as the physiological and statistical plausibility of the model parameters.

Time series analysis of jitter

Abstract This article concerns the time series analysis of jitter. Jitter involves small fluctuations in glottal cycle lengths. Time series analysis is the statistical processing of data that are recorded over a period of time. Conventionally, the amount of jitter in an analysis interval is estimated by a measure of dispersion of the glottal cycle lengths. The problem is that measures of dispersion only describe the fluctuations in the cycle lengths unambiguously when these are statistically independent. This means that the fluctuations are white noise and that changing the order of the cycles does not change their statistical properties. But it can be shown experimentally that neighbouring cycle lengths are not statistically independent because they are correlated. We therefore studied jitter by means of time series analysis methods. These dispense with the assumption that glottal cycle lengths are statistically independent. They make it possible to distinguish between mean- and short-term perturbations and to remove correlations between neighbouring perturbations. We studied dispersion measures of raw and whitened jitter (i.e., jitter from which correlations had been removed). Jitter time series were obtained from vowels [a], [i], [u] sustained by male and female healthy and dysphonic speakers. Results showed that the inter-speaker differences were smaller for whitened jitter than for raw jitter. Inter-speaker variability was reduced because time series analysis separated random from non-random perturbations.

Spectral models of additive and modulation noise in speech and phonatory excitation signals

The article presents spectral models of additive and modulation noise in speech. The purpose is to learn about the causes of noise in the spectra of normal and disordered voices and to gauge whether the spectral properties of the perturbations of the phonatory excitation signal can be inferred from the spectral properties of the speech signal. The approach to modeling consists of deducing the Fourier series of the perturbed speech, assuming that the Fourier series of the noise and of the clean monocycle-periodic excitation are known. The models explain published data, take into account the effects of supraglottal tremor, demonstrate the modulation distortion owing to vocal tract filtering, establish conditions under which noise cues of different speech signals may be compared, and predict the impossibility of inferring the spectral properties of the frequency modulating noise from the spectral properties of the frequency modulation noise (e.g., phonatory jitter and frequency tremor). The general conclusion is that only phonatory frequency modulation noise is spectrally relevant. Other types of noise in speech are either epiphenomenal, or their spectral effects are masked by the spectral effects of frequency modulation noise.

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 and noise levels and would thus be suited for perturbation measures in strongly irregular voice signals. As shown in Part I of this work, for low noise levels the results obtained by visual inspection from expert raters are comparable or better than those obtained with the tools presented here, at the expense of a larger amount of time devoted to searching visually for the glottal cycle lengths in the signal waveform. In this paper it is shown that results rapidly deteriorate with increasing noise. Hence, the use of a robust tool for voice analysis can give valid support to clinicians in term of reliability, reproducibility of results, and time-saving.

Estimation of vocal dysperiodicities in disordered connected speech by means of distant-sample bidirectional linear predictive analysis

The article presents an analysis of vocal dysperiodicities in connected speech produced by dysphonic speakers. The processing is based on a comparison of the present speech fragment with future and past fragments. The size of the dysperiodicity estimate is zero for periodic speech signals. A feeble increase of the vocal dysperiodicity is guaranteed to produce a feeble increase of the estimate. No spurious noise boosting occurs owing to cycle insertion and omission errors, or phonetic segment boundary artifacts. Additional objectives of the study have been investigating whether deviations from periodicity are larger or more commonplace in connected speech than in sustained vowels, and whether sentences that comprise frequent voice onsets and offsets are noisier than sentences that comprise few. The corpora contain sustained vowels as well as grammatically- and phonetically matched sentences. An acoustic marker that correlates with the perceived degree of hoarseness summarizes the size of the dysperiodicities. The marker values for sustained vowels have been highly correlated with those for connected speech, and the marker values for sentences that comprise few voiced/unvoiced transients have been highly correlated with the marker values for sentences that comprise many.

Shaping function models of the phonatory excitation signal

The phonatory excitation signal is the acoustic signal that is generated at the glottis by the vibrating vocal folds and pulsatile airflow. A shaping function model is a nonlinear memoryless input-output characteristic that transforms a simple harmonic into the desired output. The model can be fitted linearly to observed or simulated template cycles. The instantaneous values of the excitation cycle centroid, amplitude as well as length, and the cues for phonatory identity are set via distinct parameters. The synthetic phonatory excitation signal is zero on average, as well as identically zero when the glottal airflow rate is constant.

Predictable and random components of jitter

The subject of this article is the study of the deterministic and random components of jitter by means of a statistical time series model. Jitter is the small fluctuations in glottal cycle lengths. The purpose of time series analysis is to take into account the fact that glottal cycles are produced sequentially and that relations between neighbouring perturbations exist. The jitter time series model statistically represents the present perturbation as a weighted sum of past perturbations and random noise. The model is fitted to observed jitter time series by means of conventional linear methods. A discriminant analysis of jitter time series extracted from 279 sustained vocoids [a] [i] [u] shows that the jitter features which separately describe the predictable and random components better characterise healthy and dysphonic speakers than a traditional jitter feature. The conclusion is that the relations between neighbouring cycle length perturbations are an aspect of jitter independent of the scatter of the cycle lengths which is described by conventional jitter features.

Development and perceptual assessment of a synthesizer of disordered voices.

A synthesizer is based on a nonlinear wave-shaping model of the glottal area, an algebraic model of the glottal aerodynamics as well as concatenated-tube models of the trachea and vocal tract. Voice disorders are simulated by way of models of vocal frequency jitter and tremor, vocal amplitude shimmer and tremor, as well as pulsatile additive noise. Six experiments have been carried out to assess the synthesizer perceptually. Three experiments involve the perceptual categorization of male synthetic and human stimuli and one the auditory discrimination between synthetic and human tokens. A fifth experiment reports the auditory discrimination between synthetic tokens with different levels of additive and modulation noise. A sixth experiment reports the scoring by expert listeners of male synthetic stimuli on equal-appearing interval scales grade-roughness-breathiness (GRB). A first objective is to demonstrate the ability of the synthesizer to simulate vowel sounds that are valid exemplars of speech sounds produced by humans with voice disorders. A second objective is to learn how human expert raters perceptually map vocal frequency, additive and modulation noise as well as vowel categories into scores on GRB scales.

Validity of jitter measures in non-quasi-periodic voices. Part I: Perceptual and computer performances in cycle pattern recognition

Abstract The limit of about 5% for reliable quantification of jitter in sustained vowels of dysphonic voices—a widely accepted guideline—deserves critical analysis. The present study pertains to the effect of experience and training on the perceptual (visual) capability of correctly identifying periods in (highly) perturbed signals, and to a comparison of the performance of several programs for voice analysis. Synthesized realistic vowels (/a:/) with exactly known jitter (2.7%–31.5%) are used as material. After selection and training, experienced raters demonstrate excellent agreement in correctly identifying periods up to high values of jitter put in. Perceptual rating outperforms all computer programs in accuracy. Most remain reliable up to 10% jitter; one of them correctly measures up to the highest level.

Jitter in sustained and isolated sentences produced by dysphonic speakers

Jitter measures are known to discriminate between normal and dysphonic speakers. We investigated the influence of (i) speech material type (i.e. sustained vowels vs. isolated sentences); (ii) phonetic vowel quality; (iii) preprocessing; and (iv) speaker sex on the discriminatory performance of two pitch perturbation measures. The aim was to learn about the influence of experimental conditions on the output of dysphonic voice analysis systems. Two comparative studies were carried out. The first showed that as far as inter-vowel quality differences were concerned, all significant differences could be related to the idiosyncratic behaviour of several preprocessing schemes with reference to vowel quality. Intrinsic differences were canceled out by normalizing absolute jitter by the average fundamental period. As a rule of thumb preprocessing routines were more successful, the further F0 and F1 were apart. With all other experimental factors held constant, significant differences persisted between several preprocessing schemes, e.g. analysis by linear prediction failed on female voices and low-pass filtering eliminated so much fine signal details that discrimination between normal and dysphonic voices became impossible. In a second experiment, jitter values extracted from connected speech did not discriminate between normal and dysphonic speakers any more efficiently than values calculated from sustained vowels. As far as our corpora were concerned, no intrinsic superiority in the discrimination performance of connected speech as opposed to sustained vowels could be found. In the case of running speech absolute microperturbation values appeared to be higher during inter-segment transitions and during voice onset and offset.