Real-time Sound Source Separation For Music Applications

Sound source separation refers to the task of extracting individual sound sources from some number of mixtures of those sound sources. In this thesis, a novel sound source separation algorithm for musical applications is presented. It leverages the fact that the vast majority of commercially recorded music since the 1950s has been mixed down for two channel reproduction, more commonly known as stereo. The algorithm presented in Chapter 3 in this thesis requires no prior knowledge or learning and performs the task of separation based purely on azimuth discrimination within the stereo field. The algorithm exploits the use of the pan pot as a means to achieve image localisation within stereophonic recordings. As such, only an interaural intensity difference exists between left and right channels for a single source. We use gain scaling and phase cancellation techniques to expose frequency dependent nulls across the azimuth domain, from which source separation and resynthesis is carried out. The algorithm is demonstrated to be state of the art in the field of sound source separation but also to be a useful pre-process to other tasks such as music segmentation and surround sound upmixing

Independent component analysis of magnetoencephalographic signals

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Proceedings of the Fifth European Workshop on Probabilistic Graphical Models

Peer reviewe

Dynamics of the outer planets : 1992 Summer Study Program in Geophysical Fluid Dynamics

The topic this summer was "The Dynamics of the Outer Planets." Andrew Ingersoll gave an excellent review of the current understanding of the strcture of the atmospheres of Jupiter, Neptune, Saturn, and Uranus. He presented the flow structures inferred from the information gathered by the Voyager probes and other observations. The models of the circulations of the interior and of the weather layer - the jets and vortices that we see in the images - were discussed. Jun-Ichi Yano gave further discussions on vortex dynamics in the lab, analytical, and numerical models as applied to the outer planets. Finally, Andy returned with a discussion of thin atmospheres (some so thin that they disappear at night) and new approaches to the dynamics of the interiors. These lectures provided a thorough background in both the data and the theory. As usual, we had talks (or what are sometimes called interactive seminars!) from many visitors during the summer, some directly related to the main topic and others covering other new research in geophysical fluid dynamics. From these, the fellows and staff found new aras for collaborative research and new ideas which they may explore after the summer. Finally, the summer was completed with talks from the fellows on their individual research during the summer. These reports reflect the thought and energy that went into learning new topics and formulating new problems. We look forward to seeing fuller versions of these in journal articles. We gratefully acknowledge the support of the National Science Foundation and the Office of Naval Research. The assistance of Jake Peirson and Barbara Ewing-DeRemer, made the summer, once again, pleasant and easy for all.Funding was provided by the National Science Foundation under Grant No. OCE8901012

Causal Inference from Statistical Data

The so-called kernel-based tests of independence are developed for automatic causal discovery between random variables from purely observational statistical data, i.e., without intervention. Beyond the independence relations, the complexity of conditional distriubtions is used as an additional inference principle of determining the causal ordering between variables. Experiments with simulated and real-world data show that the proposed methods surpass the state-of-the-art approaches

Object Recognition

Vision-based object recognition tasks are very familiar in our everyday activities, such as driving our car in the correct lane. We do these tasks effortlessly in real-time. In the last decades, with the advancement of computer technology, researchers and application developers are trying to mimic the human's capability of visually recognising. Such capability will allow machine to free human from boring or dangerous jobs

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B

Towards efficient error detection in large-scale HPC systems

The need for computer systems to be reliable has increasingly become important as the dependence on their accurate functioning by users increases. The failure of these systems could very costly in terms of time and money. In as much as system's designers try to design fault-free systems, it is practically impossible to have such systems as different factors could affect them. In order to achieve system's reliability, fault tolerance methods are usually deployed; these methods help the system to produce acceptable results even in the presence of faults. Root cause analysis, a dependability method for which the causes of failures are diagnosed for the purpose of correction or prevention of future occurrence is less efficient. It is reactive and would not prevent the first failure from occurring. For this reason, methods with predictive capabilities are preferred; failure prediction methods are employed to predict the potential failures to enable preventive measures to be applied. Most of the predictive methods have been supervised, requiring accurate knowledge of the system's failures, errors and faults. However, with changing system components and system updates, supervised methods are ineffective. Error detection methods allows error patterns to be detected early to enable preventive methods to be applied. Performing this detection in an unsupervised way could be more effective as changes to systems or updates would less affect such a solution. In this thesis, we introduced an unsupervised approach to detecting error patterns in a system using its data. More specifically, the thesis investigates the use of both event logs and resource utilization data to detect error patterns. It addresses both the spatial and temporal aspects of achieving system dependability. The proposed unsupervised error detection method has been applied on real data from two different production systems. The results are positive; showing average detection F-measure of about 75%

Fruit Metabolism and Metabolomics

Over the past ten years, metabolomics strategies have allowed the relative or absolute quantitation of metabolite levels for the study of various biological questions in plant sciences. For fruit studies, in particular, they have participated in the identification of the genes underpinning fruit development and ripening. This book proposes examples of the current use of metabolomics studies of fruit for basic research or practical applications. It includes articles about several tropical and temperate fruit species. The studies concern fruit biochemical phenotyping, fruit metabolism during development and after harvest, including primary and specialized metabolisms, or bioactive compounds involved in fruit growth and environmental responses. The analytical strategies used are based mostly on liquid or gas chromatography coupled with mass spectrometry, but also on nuclear magnetic resonance and near-infrared spectroscopy. The effect of genotype, stages of development, or fruit tissue type on metabolomic profiles and corresponding metabolism regulations are addressed for fruit metabolism studies. The interest in combining other omics with metabolomics is also exemplified

Non-spurious correlations between genetic and linguistic diversities in the context of human evolution

This thesis concerns human diversity, arguing that it represents not just some form of noise, which must be filtered out in order to reach a deeper explanatory level, but the engine of human and language evolution, metaphorically put, the best gift Nature has made to us. This diversity must be understood in the context of (and must shape) human evolution, of which the Recent Out-of-Africa with Replacement model (ROA) is currently regarded, especially outside palaeoanthropology, as a true theory. It is argued, using data from palaeoanthropology, human population genetics, ancient DNA studies and primatology, that this model must be, at least, amended, and most probably, rejected, and its alternatives must be based on the concept of reticulation. The relationships between the genetic and linguistic diversities is complex, including interindividual genetic and behavioural differences (behaviour genetics) and inter-population differences due to common demographic, geographic and historic factors (spurious correlations), used to study (pre)historical processes. It is proposed that there also exist nonspurious correlations between genetic and linguistic diversities, due to genetic variants which can bias the process of language change, so that the probabilities of alternative linguistic states are altered. The particular hypothesis (formulated with Prof. D. R. Ladd) of a causal relationship between two human genes and one linguistic typological feature is supported by the statistical analysis of a vast database of 983 genetic variants and 26 linguistic features in 49 Old World populations, controlling for geography and known linguistic history. The general theory of non-spurious correlations between genetic and linguistic diversities is developed and its consequences and predictions analyzed. It will very probably profoundly impact our understanding of human diversity and will offer a firm footing for theories of language evolution and change. More specifically, through such a mechanism, gradual, accretionary models of language evolution are a natural consequence of post-ROA human evolutionary models. The unravellings of causal effects of inter-population genetic differences on linguistic states, mediated by complex processes of cultural evolution (biased iterated learning), will represent a major advance in our understanding of the relationship between cultural and genetic diversities, and will allow a better appreciation of this most fundamental and supremely valuable characteristic of humanity - its intrinsic diversity