Gérard Faucon

Linear and nonlinear causality between signals: methods, examples and neurophysiological applications

In this paper, we will present and review the most usual methods to detect linear and nonlinear causality between signals: linear Granger causality test (Geweke in J Am Stat Assoc 77:304–313, 1982) extended to direct causality in multivariate case (LGC), directed coherence (DCOH, Saito and Harashima in Recent advances in EEG and EMG data processing, Elsevier, Amsterdam, 1981), partial directed coherence (PDC, Sameshima and Baccala 1999) and nonlinear Granger causality test of Baek and Brock (in Working Paper University of Iowa, 1992) extended to direct causality in multivariate case (partial nonlinear Granger causality, PNGC). All these methods are tested and compared on several ARX, Poisson and nonlinear models, and on neurophysiological data (depth EEG). The results show that LGC, DCOH and PDC are not very robust in relation to nonlinear linkages but they seem to correctly find linear linkages if only the autoregressive parts are nonlinear. PNGC is extremely dependent on the choice of parameters. Moreover, LGC and PNGC may give misleading results in the case of causality on a spectral band, which is illustrated by our neurophysiological database.

Study of a voice activity detector and its influence on a noise reduction system

Abstract Some noise reduction processings, such as spectral subtraction techniques, require the learning of noise characteristics. In consequence, a Voice Activity Detector (VAD) is needed to determine noise and speech sequences. In this paper, in the case of spatially uncorrelated (or slightly correlated) noises, we introduce a new technique based on the coherence function which is used to determine a speech/noise classification algorithm. We combine it with a noise reduction technique based on the spectral subtraction and evaluate its influence. We report on results obtained on the performance of the algorithm and conclude that they are quite comparable to those obtained using a manual labelling.

Combined noise and echo reduction in hands-free systems: a survey

The modern telecommunications field is concerned with freedom and, in this context, hands-free systems offer subscribers the possibility of talking more naturally, without using a handset. This new type of use leads to new problems which were negligible in traditional telephony, namely the superposition of noise and echo on the speech signal. To solve these problems and provide a quality that is sufficient for telecommunications, combined reduction of these disturbances is required. This paper presents a summary of the solutions retained for this dual reduction in the context of mono-channel and two-channel sound pick-ups.

Analysis of auditory evoked potential parameters in the presence of radiofrequency fields using a support vector machines method.

The paper presents a study of global system for mobile (GSM) phone radio-frequency effects on human cerebral activity. The work was based on the study of auditory evoked potentials (AEPs) recorded from healthy humans and epileptic patients. The protocol allowed the comparison of AEPs recorded with or without exposure to electrical fields. Ten variables measured from AEPs were employed in the design of a supervised support vector machines classifier. The classification performance measured the classifier′s ability to discriminate features performed with or without radiofrequency exposure. Most significant features were chosen by a backward sequential selection that ranked the variables according to their pertinence for the discrimination. Finally, the most discriminating features were analysed statistically by a Wilcoxon signed rank test. For both populations, the N100 amplitudes were reduced under the influence of GSM radiofrequency (mean attenuation of −0.36μV for healthy subjects and −0.6OμV for epileptic patients). Healthy subjects showed a NIOO latency decrease (−5.23ms in mean), which could be consistent with mild, localised heating. The auditory cortical activity in humans was modified by GSM phone radio-frequencies, but an effect on brain functionality has not been proven.

A two-sensor noise reduction system: applications for hands-free car kit

This paper presents a two-microphone speech enhancer designed to remove noise in hands-free car kits. The algorithm, based on the magnitude squared coherence, uses speech correlation and noise decorrelation to separate speech from noise. The remaining correlated noise is reduced using cross-spectral subtraction. Particular attention is focused on the estimation of the different spectral densities (noise and noisy signals power spectral densities) which are critical for the quality of the algorithm. We also propose a continuous noise estimation, avoiding the need of vocal activity detector. Results on recorded signals are provided, showing the superiority of the two-sensor approach to single microphone techniques.

How to improve acoustic echo and noise cancelling using a single talk detector

Abstract This paper deals with speech enhancement for hands-free audio terminals, including two major problems: noise reduction and acoustic echo cancellation. Our objective is to combine a noise reduction system and an acoustic echo canceller to get a near-end speech signal with a minimum distortion and low levels of echo and noise. We present four structures (using one or two microphones and one loudspeaker) where the operation of echo cancellation comes before that of noise reduction. Generally, the noise reduction system is derived from the output of the acoustic echo canceller. An alternative is to derive the noise reduction directly from the microphone observation in order to decrease the distortion on the near-end speech signal. Experimental results are presented. Finally, in the mono-channel situation, an optimized structure controlled by an echo detector is proposed and tested.

Scalp localization of human auditory cortical activity modified by GSM electromagnetic fields

Purpose: This study attempted to determine whether there is a localized effect of GSM (Global System for Mobile communications) microwaves by studying the Auditory Evoked Potentials (AEP) recorded at the scalp of nine healthy subjects and six epileptic patients. Materials and methods: We determined the influence of GSM RadioFrequency (RF) on parameters characterizing the AEP in time or/and frequency domains. A parameter selection method using SVM (Support Vector Machines)-based criteria allowed us to estimate those most altered by the radiofrequencies. The topography of the parameter modifications was computed to determine the localization of the radiofrequency influence. A statistical test was conducted for selected scalp areas, in order to determine whether there were significant localized alterations due to the RF. Results: The epileptic patients showed a lengthening of the scalp component N100 (100 ms latency) in the frontal area contralateral to the radiation, which may be due to an afferent tract alteration. For the healthy subjects, an amplitude increase of the P200 wave (200 ms latency) was identified in the frontal area. Conclusions: The present study suggests that radiofrequency fields emitted by mobile phones modify the AEP. Nevertheless, no direct link between these findings and RF-induced damages in brain function was established.

Evaluation of two computational models of amplitude modulation coding in the inferior colliculus

Two computational models replicating amplitude-modulation encoding in the inferior colliculus (IC) are presented and compared. Neurons in this nucleus are modeled as point neurons using Mc Gregor equations, and receive depolarizing currents from action potentials delivered by stellate cells (chopper units) in the cochlear nucleus (CN). Stellate cells are modeled using modified Hodgkin-Huxley equations and receive inputs from a peripheral auditory model. The CN models of the two proposed architectures are characterized by an important dispersion of cellular characteristics, and therefore by various cellular best modulation frequencies (BMFs) ranging from 60 to 300 Hz. In contrast with the previous model proposed by [M.J. Hewitt, R. Meddis, A computer model of amplitude-modulation sensitivity of single units in the inferior colliculus, J. Acoust. Soc. Am. 95 (1994) 2145], each IC cell model receives convergent input from stellate cells with various BMFs. This approach assumes therefore minimal constraints on the model architecture and cell characteristics. The two models differ in terms of the neuronal structure of the IC, composed of 1 or 2 layers of point neurons acting as coincidence detectors. Each model is evaluated using two metrics: mean firing rate and modulation gain. Rate and temporal modulation transfer functions (r-MTFs and t-MTFs, respectively) are simulated and compared with physiological data. Simulations reveal that (i) an important dispersion of BMFs in the CN cells providing input to IC cells yields plausible IC cells responses to AM stimuli, (ii) the 2-layer IC structure yields the best approximation of IC responses measured in vivo.

Control of an adaptive echo canceller using a near-end speech detector

Abstract In the context of hands-free mobile telephony, acoustic echo cancellation (AEC) remains an important problem to deal with. This work addresses the study of an acoustic echo canceller controlled by a near-end speech detector. As a matter of fact, the echo canceller is an adaptive filter whose coefficients are disturbed by the presence of speech coming from the near-end speaker. Consequently, it is useful to stop the adaptation when this signal is detected to get a better estimation of the echo (far-end speaker). In this paper, a near-end speech detector based on the partial coherence – computed from the observations received by two microphones conditioned on the signal emitted by the loudspeaker – is investigated. To improve the performance of the AEC system, two approaches performing a saving of the AEC coefficients are proposed. The system is assessed through the power of the residual echo.

STUDY OF A NOISE CANCELLATION SYSTEM BASED ON THE COHERENCE FUNCTION

We are concerned by the problem of a signal estimation when two observations “signal + noise” are available, with a view to the enhancement of a noisy speech signal for mobile radio applications. We assume that, on one hand the coherence function between the speech signals is close to one in module, and on the other hand the coherence function between the received noises is rather weak. Recently, we presented a method based on this estimated function to weight one of the observations. The aim of this paper is to study theoretically this method to get an information on its attainable performances. After the examination of the ideal case, we consider the situation where several observations are available. Finally, we investigate the case where the hypotheses on the coherence are not really verified.