Speech recognition using ad-hoc microphone arrays

While close talking microphones give the best signal quality and produce the highest accuracy from current Automatic Speech Recognition (ASR) systems, the speech signal enhanced by microphone array has been shown to be an effective alternative in a noisy environment. The use of microphone arrays in contrast to close talking microphones alleviates the feeling of discomfort and distraction to the user. For this reason, microphone arrays are popular and have been used in a wide range of applications such as teleconferencing, hearing aids, speaker tracking, and as the front-end to speech recognition systems. With advances in sensor and sensor network technology, there is considerable potential for applications that employ ad-hoc networks of microphone-equipped devices collaboratively as a virtual microphone array. By allowing such devices to be distributed throughout the users’ environment, the microphone positions are no longer constrained to traditional fixed geometrical arrangements. This flexibility in the means of data acquisition allows different audio scenes to be captured to give a complete picture of the working environment. In such ad-hoc deployment of microphone sensors, however, the lack of information about the location of devices and active speakers poses technical challenges for array signal processing algorithms which must be addressed to allow deployment in real-world applications. While not an ad-hoc sensor network, conditions approaching this have in effect been imposed in recent National Institute of Standards and Technology (NIST) ASR evaluations on distant microphone recordings of meetings. The NIST evaluation data comes from multiple sites, each with different and often loosely specified distant microphone configurations. This research investigates how microphone array methods can be applied for ad-hoc microphone arrays. A particular focus is on devising methods that are robust to unknown microphone placements in order to improve the overall speech quality and recognition performance provided by the beamforming algorithms. In ad-hoc situations, microphone positions and likely source locations are not known and beamforming must be achieved blindly. There are two general approaches that can be employed to blindly estimate the steering vector for beamforming. The first is direct estimation without regard to the microphone and source locations. An alternative approach is instead to first determine the unknown microphone positions through array calibration methods and then to use the traditional geometrical formulation for the steering vector. Following these two major approaches investigated in this thesis, a novel clustered approach which includes clustering the microphones and selecting the clusters based on their proximity to the speaker is proposed. Novel experiments are conducted to demonstrate that the proposed method to automatically select clusters of microphones (ie, a subarray), closely located both to each other and to the desired speech source, may in fact provide a more robust speech enhancement and recognition than the full array could.

Hand somatosensory sub-cortical sources arehypoactive in migraine interictally: a functionalsource separation analysis

Background: Recent morpho-functional evidences pointed out that abnormalities in the thalamus could play a major role in the expression of migraine neurophysiological and clinical correlates. Whether this phenomenon is primary or secondary to its functional disconnection from the brain stem remains to be determined.Aim: We used a Functional Source Separation algorithmof EEG signal to extract the activity of the different neuronal pools recruited at different latencies along the somatosensory pathway in interictal migraine without aura(MO) patients. Method: Twenty MO patients and 20 healthy volunteers(HV) underwent EEG recording. Four ad-hoc functional constraints, two sub-cortical (FS14 at brain stem andFS16 at thalamic level) and two cortical (FS20 radial andFS22 tangential parietal sources), were used to extract the activity of successive stages of somatosensory information processing in response to the separate left and right median nerve electric stimulation. A band-pass digital filter (450–750 Hz) was applied offline in order to extract high-frequency oscillatory (HFO) activity from the broadband EEG signal. Results: In both stimulated sides, significant reduced subcortical brain stem (FS14) and thalamic (FS16) HFO activations characterized MO patients when compared with HV. No difference emerged in the two cortical HFO activations between two groups. Conclusion: Present results are the first neurophysiological evidence supporting the hypothesis that a functional disconnection of the thalamus from the subcortical monoaminergicsystem may underline the interictal cortical abnormal information processing in migraine. Further studiesare needed to investigate the precise directional connectivity across the entire primary subcortical and cortical somatosensory pathway in interictal MO.

Immobilized Microalgae for Nutrient Recovery from Source Separated Urine

Shortages in supply of nutrients and freshwater for a growing human population are critical global issues. Traditional centralized sewage treatment can prevent eutrophication and provide sanitation, but is neither efficient nor sustainable in terms of water and resources. Source separation of household wastes, combined with decentralized resource recovery, presents a novel approach to solve these issues. Urine contains within 1 % of household waste water up to 80 % of the nitrogen (N) and 50 % of the phosphorus (P). Since microalgae are efficient at nutrient uptake, growing these organisms in urine might be a promising technology to concomitantly clean urine and produce valuable biomass containing the major plant nutrients. While state-of-the-art suspension systems for algal cultivation have mayor shortcomings in their application, immobilized cultivation on Porous Substrate Photobioreactors (PSBRs) might be a feasible alternative. The aim of this study was to develop a robust process for nutrient recovery from minimally diluted human urine using microalgae on PSBRs. The green alga Desmodesmus abundans strain CCAC 3496 was chosen for its good growth, after screening 96 algal strains derived from urine-specific isolations and culture collections. Treatment of urine, 1:1 diluted with tap water and without addition of nutrients, was performed at a light intensity of 600 μmol photons m-2 s-1 with 2.5 % CO2 and at pH 6.5. A growth rate of 7.2 g dry weight m-² day-1 and removal efficiencies for N and P of 13.1 % and 94.1 %, respectively, were determined. Pre-treatment of urine with activated carbon was found to eliminate possible detrimental effects of pharmaceuticals. These results provide a basis for further development of the technology at pilot-scale. If found to be safe in terms human and environmental health, the biomass produced from three persons could provide the P for annual production of 31 kg wheat grain and 16 kg soybean, covering the caloric demand in food for almost one month of the year for such a household. In combination with other technologies, PSBRs could thus be applied in a decentralized resource recovery system, contributing to locally close the link between sanitation and food production.

Auditory spatial acuity approximates the resolving power of space-specific neurons

The relationship between neuronal acuity and behavioral performance was assessed in the barn owl (Tyto alba), a nocturnal raptor renowned for its ability to localize sounds and for the topographic representation of auditory space found in the midbrain. We measured discrimination of sound-source separation using a newly developed procedure involving the habituation and recovery of the pupillary dilation response. The smallest discriminable change of source location was found to be about two times finer in azimuth than in elevation. Recordings from neurons in its midbrain space map revealed that their spatial tuning, like the spatial discrimination behavior, was also better in azimuth than in elevation by a factor of about two. Because the PDR behavioral assay is mediated by the same circuitry whether discrimination is assessed in azimuth or in elevation, this difference in vertical and horizontal acuity is likely to reflect a true difference in sensory resolution, without additional confounding effects of differences in motor performance in the two dimensions. Our results, therefore, are consistent with the hypothesis that the acuity of the midbrain space map determines auditory spatial discrimination.

The detection of incipient faults in small multi-cylinder diesel engines using multiple acoustic emission sensors

This thesis investigates condition monitoring (CM) of diesel engines using acoustic emission (AE) techniques. The AE signals recorded from a small size diesel engine are mixtures of multiple sources from multiple cylinders. Thus, it is difficult to interpret the information conveyed in the signals for CM purposes. This thesis develops a series of practical signal processing techniques to overcome this problem. Various experimental studies conducted to assess the CM capabilities of AE analysis for diesel engines. A series of modified signal processing techniques were proposed. These techniques showed promising results of capability for CM of multiple cylinders diesel engine using multiple AE sensors.

Modeling High-Dimensional Audio Sequences with Recurrent Neural Networks

Cette thèse étudie des modèles de séquences de haute dimension basés sur des réseaux de neurones récurrents (RNN) et leur application à la musique et à la parole. Bien qu'en principe les RNN puissent représenter les dépendances à long terme et la dynamique temporelle complexe propres aux séquences d'intérêt comme la vidéo, l'audio et la langue naturelle, ceux-ci n'ont pas été utilisés à leur plein potentiel depuis leur introduction par Rumelhart et al. (1986a) en raison de la difficulté de les entraîner efficacement par descente de gradient. Récemment, l'application fructueuse de l'optimisation Hessian-free et d'autres techniques d'entraînement avancées ont entraîné la recrudescence de leur utilisation dans plusieurs systèmes de l'état de l'art. Le travail de cette thèse prend part à ce développement. L'idée centrale consiste à exploiter la flexibilité des RNN pour apprendre une description probabiliste de séquences de symboles, c'est-à-dire une information de haut niveau associée aux signaux observés, qui en retour pourra servir d'à priori pour améliorer la précision de la recherche d'information. Par exemple, en modélisant l'évolution de groupes de notes dans la musique polyphonique, d'accords dans une progression harmonique, de phonèmes dans un énoncé oral ou encore de sources individuelles dans un mélange audio, nous pouvons améliorer significativement les méthodes de transcription polyphonique, de reconnaissance d'accords, de reconnaissance de la parole et de séparation de sources audio respectivement. L'application pratique de nos modèles à ces tâches est détaillée dans les quatre derniers articles présentés dans cette thèse. Dans le premier article, nous remplaçons la couche de sortie d'un RNN par des machines de Boltzmann restreintes conditionnelles pour décrire des distributions de sortie multimodales beaucoup plus riches. Dans le deuxième article, nous évaluons et proposons des méthodes avancées pour entraîner les RNN. Dans les quatre derniers articles, nous examinons différentes façons de combiner nos modèles symboliques à des réseaux profonds et à la factorisation matricielle non-négative, notamment par des produits d'experts, des architectures entrée/sortie et des cadres génératifs généralisant les modèles de Markov cachés. Nous proposons et analysons également des méthodes d'inférence efficaces pour ces modèles, telles la recherche vorace chronologique, la recherche en faisceau à haute dimension, la recherche en faisceau élagué et la descente de gradient. Finalement, nous abordons les questions de l'étiquette biaisée, du maître imposant, du lissage temporel, de la régularisation et du pré-entraînement.

Automatic artefact removal from event-related potentials via clustering

This paper outlines a method for automatic artefact removal from multichannel recordings of event-related potentials (ERPs). The proposed method is based on, firstly, separation of the ERP recordings into independent components using the method of temporal decorrelation source separation (TDSEP). Secondly, the novel lagged auto-mutual information clustering (LAMIC) algorithm is used to cluster the estimated components, together with ocular reference signals, into clusters corresponding to cerebral and non-cerebral activity. Thirdly, the components in the cluster which contains the ocular reference signals are discarded. The remaining components are then recombined to reconstruct the clean ERPs.

Hushållsavfall i Borlänge kommun : analyser av material en och flerfamiljshus

In Borlänge, source separation has been the basis for management of household waste for over five years. This report reviews today?s system and gives a model for further follow-up through waste grouping. In the basic system waste is separated into three fractions: biodegradable, waste to energy and waste to landfill. All waste is packed in plastic bags, put in separate containers for each fraction, and collected from the property. Separate analyses were made of waste from single family houses and apartment buildings. The amount of waste per household and week, number of non-sorted bags, purity, recovery rate and density of each fraction was calculated. The amount of packaging collected together with the household waste is given. Material collected under the Swedish law of Producers? Responsibility is not covered in this report.

Chaos-based communication systems in non-ideal channels

Recently, many chaos-based communication systems have been proposed. They can present the many interesting properties of spread spectrum modulations. Besides, they can represent a low-cost increase in security. However, their major drawback is to have a Bit Error Rate (BER) general performance worse than their conventional counterparts. In this paper, we review some innovative techniques that can be used to make chaos-based communication systems attain lower levels of BER in non-ideal environments. In particular, we succinctly describe techniques to counter the effects of finite bandwidth, additive noise and delay in the communication channel. Although much research is necessary for chaos-based communication competing with conventional techniques, the presented results are auspicious. (C) 2011 Elsevier B. V. All rights reserved.

High precision range estimation techniques for multi-path wireless environments

Range estimation is the core of many positioning systems such as radar, and Wireless Local Positioning Systems (WLPS). The estimation of range is achieved by estimating Time-of-Arrival (TOA). TOA represents the signal propagation delay between a transmitter and a receiver. Thus, error in TOA estimation causes degradation in range estimation performance. In wireless environments, noise, multipath, and limited bandwidth reduce TOA estimation performance. TOA estimation algorithms that are designed for wireless environments aim to improve the TOA estimation performance by mitigating the effect of closely spaced paths in practical (positive) signal-to-noise ratio (SNR) regions. Limited bandwidth avoids the discrimination of closely spaced paths. This reduces TOA estimation performance. TOA estimation methods are evaluated as a function of SNR, bandwidth, and the number of reflections in multipath wireless environments, as well as their complexity. In this research, a TOA estimation technique based on Blind signal Separation (BSS) is proposed. This frequency domain method estimates TOA in wireless multipath environments for a given signal bandwidth. The structure of the proposed technique is presented and its complexity and performance are theoretically evaluated. It is depicted that the proposed method is not sensitive to SNR, number of reflections, and bandwidth. In general, as bandwidth increases, TOA estimation performance improves. However, spectrum is the most valuable resource in wireless systems and usually a large portion of spectrum to support high performance TOA estimation is not available. In addition, the radio frequency (RF) components of wideband systems suffer from high cost and complexity. Thus, a novel, multiband positioning structure is proposed. The proposed technique uses the available (non-contiguous) bands to support high performance TOA estimation. This system incorporates the capabilities of cognitive radio (CR) systems to sense the available spectrum (also called white spaces) and to incorporate white spaces for high-performance localization. First, contiguous bands that are divided into several non-equal, narrow sub-bands that possess the same SNR are concatenated to attain an accuracy corresponding to the equivalent full band. Two radio architectures are proposed and investigated: the signal is transmitted over available spectrum either simultaneously (parallel concatenation) or sequentially (serial concatenation). Low complexity radio designs that handle the concatenation process sequentially and in parallel are introduced. Different TOA estimation algorithms that are applicable to multiband scenarios are studied and their performance is theoretically evaluated and compared to simulations. Next, the results are extended to non-contiguous, non-equal sub-bands with the same SNR. These are more realistic assumptions in practical systems. The performance and complexity of the proposed technique is investigated as well. This study’s results show that selecting bandwidth, center frequency, and SNR levels for each sub-band can adapt positioning accuracy.

COSIMA calibration for the detection and characterization of the cometary solid organic matter

On the orbiter of the Rosetta spacecraft, the Cometary Secondary Ion Mass Analyser (COSIMA) will provide new in situ insights about the chemical composition of cometary grains all along 67P/Churyumov–Gerasimenko (67P/CG) journey until the end of December 2015 nominally. The aim of this paper is to present the pre-calibration which has already been performed as well as the different methods which have been developed in order to facilitate the interpretation of the COSIMA mass spectra and more especially of their organic content. The first step was to establish a mass spectra library in positive and negative ion mode of targeted molecules and to determine the specific features of each compound and chemical family analyzed. As the exact nature of the refractory cometary organic matter is nowadays unknown, this library is obviously not exhaustive. Therefore this library has also been the starting point for the research of indicators, which enable to highlight the presence of compounds containing specific atom or structure. These indicators correspond to the intensity ratio of specific peaks in the mass spectrum. They have allowed us to identify sample containing nitrogen atom, aliphatic chains or those containing polyaromatic hydrocarbons. From these indicators, a preliminary calibration line, from which the N/C ratio could be derived, has also been established. The research of specific mass difference could also be helpful to identify peaks related to quasi-molecular ions in an unknown mass spectrum. The Bayesian Positive Source Separation (BPSS) technique will also be very helpful for data analysis. This work is the starting point for the analysis of the cometary refractory organic matter. Nevertheless, calibration work will continue in order to reach the best possible interpretation of the COSIMA observations.

Inheritance of early Archaean Pb-isotope variability from long-lived Hadean protocrust

Comparison of initial Pb-isotope signatures of several early Archaean (3.65-3.82 Ga) lithologies (orthogneisses and metasediments) and minerals (feldspar and galena) documents the existence of substantial isotopic heterogeneity in the early Archaean, particularly in the Pb-207/Pb-204 ratio. The magnitude of isotopic variability at 3.82-3.65 Ga requires source separation between 4.3 and 4.1 Ga, depending on the extent of U/Pb fractionation possible in the early Earth. The isotopic heterogeneity could reflect the coexistence of enriched and depleted mantle domains or the separation of a terrestrial protocrust with a U-238/Pb-204 (mu) that was ca. 20-30% higher than coeval mantle. We prefer this latter explanation because the high-p signature is most evident in metasediments (that formed at the Earth's surface). This interpretation is strengthened by the fact that no straightforward mantle model can be constructed for these high-mu lithologies without violating bulk silicate Earth constraints. The Pb-isotope evidence for a long-lived protocrust complements similar Hf-isotope data from the Earth's oldest zircons, which also require an origin from an enriched (low Lu/Hf) environment. A model is developed in which greater than or equal to3.8-Ga tonalite and monzodiorite gneiss precursors (for one of which we provide zircon U-Pb data) are not mantle-derived but formed by remelting or differentiation of ancient (ca. 4.3 Ga) basaltic crust which had evolved with a higher U/Pb ratio than coeval mantle in the absence of the subduction process. With the initiation of terrestrial subduction at, we propose, ca. 3.75 Ga, most of the greater than or equal to3.8-Ga basaltic shell (and its differentiation products) was recycled into the mantle, because of the lack of a stabilising mantle lithosphere. We argue that the key event for preservation of all greater than or equal to3.8-Ga terrestrial crust was the intrusion of voluminous granitoids immediately after establishment of global subduction because of complementary creation of a lithospheric keel. Furthermore, we argue that preservation of !3.8-Ga material (in situ rocks and zircons) globally is restricted to cratons with a high U/Pb source character (North Atlantic, Slave, Zimbabwe, Yilgarn, and Wyoming), and that the Pb-isotope systematics of these provinces are ultimately explained by reworking of material that was derived from ca. 4.3 Ga (i.e. Hadean) basaltic crust.

Multiple frequency functional connectivity in the hand somatosensory network:an EEG study

Objective: To investigate the dynamics of communication within the primary somatosensory neuronal network. Methods: Multichannel EEG responses evoked by median nerve stimulation were recorded from six healthy participants. We investigated the directional connectivity of the evoked responses by assessing the Partial Directed Coherence (PDC) among five neuronal nodes (brainstem, thalamus and three in the primary sensorimotor cortex), which had been identified by using the Functional Source Separation (FSS) algorithm. We analyzed directional connectivity separately in the low (1-200. Hz, LF) and high (450-750. Hz, HF) frequency ranges. Results: LF forward connectivity showed peaks at 16, 20, 30 and 50. ms post-stimulus. An estimate of the strength of connectivity was modulated by feedback involving cortical and subcortical nodes. In HF, forward connectivity showed peaks at 20, 30 and 50. ms, with no apparent feedback-related strength changes. Conclusions: In this first non-invasive study in humans, we documented directional connectivity across subcortical and cortical somatosensory pathway, discriminating transmission properties within LF and HF ranges. Significance: The combined use of FSS and PDC in a simple protocol such as median nerve stimulation sheds light on how high and low frequency components of the somatosensory evoked response are functionally interrelated in sustaining somatosensory perception in healthy individuals. Thus, these components may potentially be explored as biomarkers of pathological conditions. © 2012 International Federation of Clinical Neurophysiology.

Impaired brainstem and thalamic high-frequency oscillatory EEG activity in migraine between attacks

INTRODUCTION: We investigated whether interictal thalamic dysfunction in migraine without aura (MO) patients is a primary determinant or the expression of its functional disconnection from proximal or distal areas along the somatosensory pathway. METHODS: Twenty MO patients and twenty healthy volunteers (HVs) underwent an electroencephalographic (EEG) recording during electrical stimulation of the median nerve at the wrist. We used the functional source separation algorithm to extract four functionally constrained nodes (brainstem, thalamus, primary sensory radial, and primary sensory motor tangential parietal sources) along the somatosensory pathway. Two digital filters (1-400 Hz and 450-750 Hz) were applied in order to extract low- (LFO) and high- frequency (HFO) oscillatory activity from the broadband signal. RESULTS: Compared to HVs, patients presented significantly lower brainstem (BS) and thalamic (Th) HFO activation bilaterally. No difference between the two cortical HFO as well as in LFO peak activations between the two groups was seen. The age of onset of the headache was positively correlated with HFO power in the right brainstem and thalamus. CONCLUSIONS: This study provides evidence for complex dysfunction of brainstem and thalamocortical networks under the control of genetic factors that might act by modulating the severity of migraine phenotype.