233 research outputs found

    Audio Indexing Including Frequency Tracking of Simultaneous Multiple Sources in Speech and Music

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    National audienceIn this paper, we present a complete system for audio indexing. This system is based state-of-the-art methods of Speech-Music-Noise segmentation and Monophonic/Polyphonic estimation. After those methods we propose an original system of superposed sources detection. This approach is based on the analysis of the evolution of the predominant frequencies. In order to validate the whole system we used different corpora : Radio broadcasts, studio music and degraded field records. The first results are encouraging and show the potential of our approach which is generic and can be used on both music and speech contents

    Intérêt du suivi de fréquences pour la détection de sources harmoniques multiples

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    National audienceDans cet article, nous présentons une nouvelle approche pour la localisation de superposition de sources harmoniques. Notre méthode est basée sur le suivi des fréquence prédominantes du signal afin de former des segments sinusoïdaux. Les relations entre les fréquences de ces derniers sont ensuite étudiées afin de regrouper les segments sinusoïdaux appartenant à une même source. Les sources étant localisées sur le plan temps-fréquence, les zones où coexistent différentes sources sont finalement extraites. Notre approche à été testée à la fois sur des contenus de parole et de musique avec des résultats prometteurs

    Wave Field Synthesis in a listening room

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    This thesis investigates the influence of the listening room on sound fields synthesised by Wave Field Synthesis. Methods are developed that allow for investigation of the spatial and timbral perception of Wave Field Synthesis in a reverberant environment using listening experiments based on simulation by binaural synthesis and room acoustical simulation. The results can serve as guidelines for the design of listening rooms for Wave Field Synthesis.Diese Dissertation untersucht den Einfluss des Wiedergaberaums auf Schallfelder, die mit Wellenfeldsynthese synthetisiert werden. Es werden Methoden zur Untersuchung von räumlicher und klangfarblicher Wahrnehmung von Wellenfeldsynthese in einer reflektierenden Umgebung mittels Hörversuchen entwickelt, die auf Simulation mit Binauralsynthese und raumakustischer Simulation beruhen. Die Ergebnisse können als Richtlinien zur Gestaltung von Wiedergaberäumen für Wellenfeldsynthese dienen

    Analysis of Modulated Multivariate Oscillations

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    The concept of a common modulated oscillation spanning multiple time series is formalized, a method for the recovery of such a signal from potentially noisy observations is proposed, and the time-varying bias properties of the recovery method are derived. The method, an extension of wavelet ridge analysis to the multivariate case, identifies the common oscillation by seeking, at each point in time, a frequency for which a bandpassed version of the signal obtains a local maximum in power. The lowest-order bias is shown to involve a quantity, termed the instantaneous curvature, which measures the strength of local quadratic modulation of the signal after demodulation by the common oscillation frequency. The bias can be made to be small if the analysis filter, or wavelet, can be chosen such that the signal's instantaneous curvature changes little over the filter time scale. An application is presented to the detection of vortex motions in a set of freely-drifting oceanographic instruments tracking the ocean currents

    Intelligent Sensing and Learning for Advanced MIMO Communication Systems

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    AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

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    This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

    Oscillations of Sensitivity and Response Bias in Auditory Perception

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    Many behavioural measures of visual perception show continuous rhythmic fluctuations that reflect the influence of neural oscillations in the theta (4-7 Hz) and alpha frequency band (7-12 Hz). This thesis examines whether similar behavioural oscillations exist in audition and if so, how they may be linked to attention and sensory expectation. Three experiments are reported. All employed a similar design that involved the identification of the pitch (Experiment 1) or the ear of origin of a brief, monaural sinusoidal tone masked by uncorrelated broadband noise (Experiment 2 and 3). Experiment 1 confirmed oscillations in auditory sensitivity and revealed, for the first time, rhythmic fluctuations also in response bias. Sensitivity fluctuated at ~6 Hz, while bias exhibited slightly higher frequencies, ~8 Hz. The antiphase characteristic of the sensitivity oscillations between the ears were consistent with spatial attentional sampling. Additional results from Experiment 2 and 3 showed that oscillations in bias at ~9 Hz are related to sensory expectation arising from recent stimulus history. In particular, the oscillations in bias depended on the previous target occurring in the same ear as the current one. This suggests that sensory expectation is communicated through ear- or location-specific reverberations in the alpha band. Additionally, Experiment 3 revealed a new oscillatory effect in auditory behaviour related to unexpected stimulus changes: one trial after an infrequent target occurred, accuracy fluctuated rhythmically at ~7 Hz. These findings highlight the strong influence of oscillatory neural activity on auditory perception. In particular, they show that neural oscillations underlie important aspects necessary to maintain a continuous and coherent percept of the world, by anticipating forthcoming sensory input, sampling the relevant information and updating internal predictions
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