A Study on Linear Blind Source Separation using Associative Memory Model

早大学位記番号:新7630早稲田大

Complex Neural Networks for Audio

Audio is represented in two mathematically equivalent ways: the real-valued time domain (i.e., waveform) and the complex-valued frequency domain (i.e., spectrum). There are advantages to the frequency-domain representation, e.g., the human auditory system is known to process sound in the frequency-domain. Furthermore, linear time-invariant systems are convolved with sources in the time-domain, whereas they may be factorized in the frequency-domain. Neural networks have become rather useful when applied to audio tasks such as machine listening and audio synthesis, which are related by their dependencies on high quality acoustic models. They ideally encapsulate fine-scale temporal structure, such as that encoded in the phase of frequency-domain audio, yet there are no authoritative deep learning methods for complex audio. This manuscript is dedicated to addressing the shortcoming. Chapter 2 motivates complex networks by their affinity with complex-domain audio, while Chapter 3 contributes methods for building and optimizing complex networks. We show that the naive implementation of Adam optimization is incorrect for complex random variables and show that selection of input and output representation has a significant impact on the performance of a complex network. Experimental results with novel complex neural architectures are provided in the second half of this manuscript. Chapter 4 introduces a complex model for binaural audio source localization. We show that, like humans, the complex model can generalize to different anatomical filters, which is important in the context of machine listening. The complex model\u27s performance is better than that of the real-valued models, as well as real- and complex-valued baselines. Chapter 5 proposes a two-stage method for speech enhancement. In the first stage, a complex-valued stochastic autoencoder projects complex vectors to a discrete space. In the second stage, long-term temporal dependencies are modeled in the discrete space. The autoencoder raises the performance ceiling for state of the art speech enhancement, but the dynamic enhancement model does not outperform other baselines. We discuss areas for improvement and note that the complex Adam optimizer improves training convergence over the naive implementation

Quantifying the psychological properties of words

This thesis explores the psychological properties of words – the idea that words carry links to additional information beyond their dictionary meaning. It does so by presenting three distinct publications and an applied project, the Macroscope. The published research respectively covers: the modelling of language networks to explain lexical growth; the use of high dimensional vector representations of words to discuss language learning; and the collection of a normative dataset of single word humour ratings. The first publication outlines the use of network science in psycholinguistics. The methodology is discussed, providing clear guidelines on the application of networks when answering psychologically motivated questions. A selection of psychological studies is presented as a demonstration of use cases for networks in cognitive psychology. The second publication uses referent feature norms to represent words in a high dimensional vector space. A correlative link between referent distinctiveness and age of acquisition is proposed. The shape bias literature (the idea that children only pay attention to the shape of objects early on) is evaluated in relation to the findings. The third publication collects and shares a normative dataset of single word humour ratings. Descriptive properties of the dataset are outlined and the potential future use in the field of humour is discussed. Finally, the thesis presents the Macroscope, a collaborative project put together with Li Ying. The Macroscope is an online platform, allowing for easy analysis of the psychological properties of target words. The platform is showcased, and its full functionality is presented, including visualisation examples. Overall, the thesis aims to give researchers all that’s necessary to start working with psychological properties of words – the understanding of network science in psycholinguistics, high dimensional vector spaces, normative datasets and the applied use of all the above through the Macroscope

Functional Brain Oscillations: How Oscillations Facilitate Information Representation and Code Memories

The overall aim of the modelling works within this thesis is to lend theoretical evidence to empirical findings from the brain oscillations literature. We therefore hope to solidify and expand the notion that precise spike timing through oscillatory mechanisms facilitates communication, learning, information processing and information representation within the brain. The primary hypothesis of this thesis is that it can be shown computationally that neural de-synchronisations can allow information content to emerge. We do this using two neural network models, the first of which shows how differential rates of neuronal firing can indicate when a single item is being actively represented. The second model expands this notion by creating a complimentary timing mechanism, thus enabling the emergence of qualitive temporal information when a pattern of items is being actively represented. The secondary hypothesis of this thesis is that it can be also be shown computationally that oscillations might play a functional role in learning. Both of the models presented within this thesis propose a sparsely coded and fast learning hippocampal region that engages in the binding of novel episodic information. The first model demonstrates how active cortical representations enable learning to occur in their hippocampal counterparts via a phase-dependent learning rule. The second model expands this notion, creating hierarchical temporal sequences to encode the relative temporal position of cortical representations. We demonstrate in both of these models, how cortical brain oscillations might provide a gating function to the representation of information, whilst complimentary hippocampal oscillations might provide distinct phasic reference points for learning

Word Knowledge and Word Usage

Word storage and processing define a multi-factorial domain of scientific inquiry whose thorough investigation goes well beyond the boundaries of traditional disciplinary taxonomies, to require synergic integration of a wide range of methods, techniques and empirical and experimental findings. The present book intends to approach a few central issues concerning the organization, structure and functioning of the Mental Lexicon, by asking domain experts to look at common, central topics from complementary standpoints, and discuss the advantages of developing converging perspectives. The book will explore the connections between computational and algorithmic models of the mental lexicon, word frequency distributions and information theoretical measures of word families, statistical correlations across psycho-linguistic and cognitive evidence, principles of machine learning and integrative brain models of word storage and processing. Main goal of the book will be to map out the landscape of future research in this area, to foster the development of interdisciplinary curricula and help single-domain specialists understand and address issues and questions as they are raised in other disciplines

Image and Evidence: The Study of Attention through the Combined Lenses of Neuroscience and Art

: Levy, EK 2012, ‘An artistic exploration of inattention blindness’, in Frontiers Hum Neurosci, vol. 5, ISSN=1662-5161.Full version unavailable due to 3rd party copyright restrictions.This study proposed that new insights about attention, including its phenomenon and pathology, would be provided by combining perspectives of the neurobiological discourse about attention with analyses of artworks that exploit the constraints of the attentional system. To advance the central argument that art offers a training ground for the attentional system, a wide range of contemporary art was analysed in light of specific tasks invoked. The kinds of cognitive tasks these works initiate with respect to the attentional system have been particularly critical to this research. Attention was explored within the context of transdisciplinary art practices, varied circumstances of viewing, new neuroscientific findings, and new approaches towards learning. Research for this dissertation required practical investigations in a gallery setting, and this original work was contextualised and correlated with pertinent neuroscientific approaches. It was also concluded that art can enhance public awareness of attention disorders and assist the public in discriminating between medical and social factors through questioning how norms of behaviour are defined and measured. This territory was examined through the comparative analysis of several diagnostic tests for attention deficit hyperactivity disorder (ADHD), through the adaptation of a methodology from economics involving patent citation in order to show market incentives, and through examples of data visualisation. The construction of an installation and collaborative animation allowed participants to experience first-hand the constraints on the attentional system, provoking awareness of our own “normal” physiological limitations. The embodied knowledge of images, emotion, and social context that are deeply embedded in art practices appeared to be capable of supplementing neuroscience’s understanding of attention and its disorders

Modeling Memes: A Memetic View of Affordance Learning

This research employed systems social science inquiry to build a synthesis model that would be useful for modeling meme evolution. First, a formal definition of memes was proposed that balanced both ontological adequacy and empirical observability. Based on this definition, a systems model for meme evolution was synthesized from Shannon Information Theory and elements of Bandura\u27s Social Cognitive Learning Theory. Research in perception, social psychology, learning, and communication were incorporated to explain the cognitive and environmental processes guiding meme evolution. By extending the PMFServ cognitive architecture, socio-cognitive agents were created who could simulate social learning of Gibson affordances. The PMFServ agent based model was used to examine two scenarios: a simulation to test for potential memes inside the Stanford Prison Experiment and a simulation of pro-US and anti-US meme competition within the fictional Hamariyah Iraqi village. The Stanford Prison Experiment simulation was designed, calibrated, and tested using the original Stanford Prison Experiment archival data. This scenario was used to study potential memes within a real-life context. The Stanford Prison Experiment simulation was complemented by internal and external validity testing. The Hamariyah Iraqi village was used to analyze meme competition in a fictional village based upon US Marine Corps human terrain data. This simulation demonstrated how the implemented system can infer the personality traits and contextual factors that cause certain agents to adopt pro-US or anti-US memes, using Gaussian mixture clustering analysis and cross-cluster analysis. Finally, this research identified significant gaps in empirical science with respect to studying memes. These roadblocks and their potential solutions are explored in the conclusions of this work

A Decade of Neural Networks: Practical Applications and Prospects

The Jet Propulsion Laboratory Neural Network Workshop, sponsored by NASA and DOD, brings together sponsoring agencies, active researchers, and the user community to formulate a vision for the next decade of neural network research and application prospects. While the speed and computing power of microprocessors continue to grow at an ever-increasing pace, the demand to intelligently and adaptively deal with the complex, fuzzy, and often ill-defined world around us remains to a large extent unaddressed. Powerful, highly parallel computing paradigms such as neural networks promise to have a major impact in addressing these needs. Papers in the workshop proceedings highlight benefits of neural networks in real-world applications compared to conventional computing techniques. Topics include fault diagnosis, pattern recognition, and multiparameter optimization

Not this, but that.' Exploring disambiguation in the context of multilingual word learning

Growing up and living with more than one language modulates new language learning in a variety of ways. Similarities and differences to monolinguals with regards to languages learning in all its aspects were found. These range from phonology to pragmatics. However, non-linguistic domains, such as cognition, can also be affected by the multilingual experience. The acquisition of words is an indispensable step in learning a language, be that one’s first or subsequent languages. To learn a word, its word form must be correctly mapped onto its meaning and then remembered. One ‘strategy’ children and adults implicitly employ to map a new label to a new item or concept is referred to as disambiguation. This mental process is analogous to the common process-of-elimination and based on the Disjunctive Syllogism. The idea is that a new label refers to a novel object in the presence of familiar items creating the support for one-to-one mappings between a word and its referent. Attaching a new label to a new label-unknown object rather than a familiar label-known object expedites vocabulary growth, especially in children. Although this mental process can be found in adults too, it was predominantly studied in the context of word learning in children, and more recently multilingual children. The interest in researching disambiguation in multilingual contexts arose as researchers began to wonder if people, who grew up and were exposed to more than one language, would exhibit the so-called disambiguation effect at all given that they know multiple labels for the same objects. The formulation of many-to-one mappings stands in opposition to one-to-one mappings mentioned above. However, does this mean that multilingual children and adults never disambiguate? The answer to this question cannot be binary, considering the myriad of direct and indirect effects multilingualism has on word learning. In this thesis, I explore the use of disambiguation in various multilingual contexts: 1. Disambiguation studies on children are usually conducted under the scope of word learning, which consists of mapping and retention of words; however, only very few studies explicitly explore the relationship between the mapping of a new word and the ability to retain it. In this first study, I explored whether and how monolingual and multilingual children’s use of disambiguation as a fast mapping constraint boosted their ability to retain this new mapping within the same experiment. For this, I designed and adapted a looking-while-listening eye-tracking paradigm to allow for data collection within a young population (aged 18 to 30 months old). I found that children from monolingual and multilingual backgrounds are able to use disambiguation as mapping strategy; however, they differ with regards to how disambiguation modulated their ability to retain the new word. Whilst the use of disambiguation positively affected monolingual children’s retention performance, children from multilingual backgrounds did not display this boosting effect. Thus, it can be said that disambiguation starts out as default mapping strategy that in some, but not other, cases develops into a more consolidated learning/retention strategy. 2. In a second study, I examined whether disambiguation as a mapping strategy is prevalent in multilingual adults and how their multilingual experience may modulate the processing speed of this process-of-elimination. Multilingualism does affect a person’s learning not only directly but also indirectly. An accumulating amount of research is currently being conducted on the mutual effects of multilingualism and executive functioning with findings addressing cognitive domains such as working memory and cognitive control. As these findings allude to differences in cognitive processing, any task requiring the contribution of these skills, such as the one in this study, one must control for these variations. In this study, I explored the individual contributions of multilingualism and executive functioning to a fast mapping and retention task. Language experience variables strongly modulated the accuracy and processing times of disambiguation and retention conditions, whereby speed-accuracy trade-offs were found. Furthermore, working memory and cognitive control impacted the accuracy and reaction times. Those with better scores on the working memory task also performed faster. Results highlight the requirement for regarding multilingualism as a multivariate spectrum in future research rather than in dichotomous categories. 3. In a third study, I extended the context of disambiguation by not only examining its use on mappings between words and objects but also on mappings between factual information and objects. Factual information about items in this study are, for instance, “this is the one I keep in the living room”. Studies with young children have shown their tendency to transfer the use of disambiguation onto other domains of language learning, such as assigning new factual information to an unfamiliar object rather than a familiar name-known object. However, it is self-evident that adults may not show this transfer of disambiguation due to their ability to draw from other forms of knowledge, such as their cognitive, semantic, and pragmatic abilities, and life experience in general. In this study, I examined how multilinguals adults’ linguistic experience impacts on the use of disambiguation in factual contexts by looking at eye-gaze data. Furthermore, I probed participants’ underlying decision-making processes by questioning their choices after specific trials. The results showed that adults do not extend disambiguation to contexts other than labels, but that language background did modulate those instances in which disambiguation took place based on contrast. In conclusion, it can be said that disambiguation is a sound strategy for making fast decisions about labels and how they attach to meaning. However, the investigations in this thesis also show that the context in which disambiguation is to be used is paramount to its success or someone’s implicit decision to rely upon it. Lastly, this thesis and its findings contribute to the modern view that multilingualism is a continuum and should be researched and regarded from a holistic angle