Representation Learning via Variational Bayesian Networks

We present Variational Bayesian Network (VBN) - a novel Bayesian entity representation learning model that utilizes hierarchical and relational side information and is particularly useful for modeling entities in the ``long-tail'', where the data is scarce. VBN provides better modeling for long-tail entities via two complementary mechanisms: First, VBN employs informative hierarchical priors that enable information propagation between entities sharing common ancestors. Additionally, VBN models explicit relations between entities that enforce complementary structure and consistency, guiding the learned representations towards a more meaningful arrangement in space. Second, VBN represents entities by densities (rather than vectors), hence modeling uncertainty that plays a complementary role in coping with data scarcity. Finally, we propose a scalable Variational Bayes optimization algorithm that enables fast approximate Bayesian inference. We evaluate the effectiveness of VBN on linguistic, recommendations, and medical inference tasks. Our findings show that VBN outperforms other existing methods across multiple datasets, and especially in the long-tail

Vocal-Affective Weaning and its role in musical enculturation: children’s interest in music beyond the Infant-Directed Register

Well-established theoretical approaches to the Infant-directed Register (IDReg) draw a more or less tacit causal relation between it and all future musical engagement: the former establishes a basis for the latter. However, a mechanistic, observable chain of events linking these two phenomena has only been assumed, remaining for the most part unproblematized and undescribed. This thesis represents a first systematic attempt to fill this theoretical and empirical gap by concretely linking early musicality and the first manifestations of the most characteristic and widespread Western form of musical engagement: listening to recorded music. It does so by introducing a new construct as a mediating motivational factor— Vocal- Affective Weaning (VAW) —which mainly concerns the variation of caregivers’ use of the IDReg across developmental time. The thesis is grounded and tested in three literature reviews, two theoretical chapters, and three empirical ones. In terms of main findings, little evidence is found to support the existence of VAW as depicted in the main thesis. Consequently, any direct relationship between VAW and toddlers' attention to recorded music seems doubtful. Instead, data evidences a progressive use of Infant-Directed Speech (IDSp) as an ostensive cue used in the context of Natural Pedagogy, which allows for a better understanding of the relative importance of affectivity and cognition as parallel, coexisting governing principles that exert an influence on developmental changes concerning parental use of IDSp. If anything, data highlights interaction as a much more promising element in an explanatory chain linking the IDReg and Western forms of music engagement. The mentioned mismatch between the main thesis and results is interpreted in terms of the former’s unjustified stress on ‘centripetal’ over ‘centrifugal’ attachment dynamics. Resulting data also allows to delineate more nuanced factorial and developmental accounts of toddlers’ sustained attention to musical stimuli than has been previously advanced.Becas-Chile Scholarship, CONICYT Chile CONICYT- Chile Cambridge Scholarship, Cambridge Commonwealth, European & International Trus

Transforming musical performance: activating the audience as digital collaborators

Digital technologies have transformed the performance practice, recording and distribution technologies, economy and sonic landscape of music in a process of change that began in the early 1980s. Recent technological developments have opened up the possibility of embodied interaction between audiences and performers, reframing music performance as a collaborative improvisatory space that affords Interactive Musical Participation. The research in this practice-based thesis looks at the relationship and experience of audience members and musicians exploring Interactive Musical Participation within the wide stylistic framework of contemporary jazz. It also studies the potential for the creation of compositional, technological and performance protocols to enable successful Interactive Musical Participation. This has been achieved through a process of mapping the methodology behind the composition, technical infrastructure, performances and post-performance analysis of a series of musical artefacts. Cook (2001 and 2009) suggests that researchers in this field should “Make a piece, not an instrument or controller” and this dictum has influenced the development of the technical infrastructure for this research. Easily accessible and low-cost digital audio workstations Ableton Live (2017) and Logic Pro X (Apple, 2019) as well as the digital protocols Open Sound Control (OSC) (Opensoundcontrol.org) have been utilised to deliver the programming and networking requirements. A major innovation stemming from this project has been the development of the Deeper Love Soundpad App, a sample playback app for Apple smartphones and iPads, in collaboration with Dr. Rob Toulson. The theoretical background to this research has been informed by actornetwork theory, the sociological approach developed by Bruno Latour (2005), Michel Callon (1986) and John Law (1992). Actor-network theory (ANT) provides a framework for understanding the mechanics of power and organisation within heterogeneous non-hierarchical networks. Mapping and analysing the ANT networks and connections created by the research performances has provided valuable data in the Interactive Musical Participatio

The Harkive Project: Popular Music, Data & Digital Technologies

This thesis is about research around Harkive, an online project designed by this researcher, which gathers stories, reflections, and other data from people about their everyday engagement with popular music. Since 2013, over 1,000 people have contributed to the project, producing around 8,000 texts and highlighting the music reception activities of contemporary music listeners. The thesis presents an analysis of the texts and other data generated, answering a key research question: What can an analysis of the data generated by The Harkive Project reveal about the music reception practices of respondents? To answer this question, the researcher developed an experimental, innovative approach that conceives of Harkive as a space in which people can reflect upon their engagement with music, whilst simultaneously acting as a place that is able to replicate many of the commercial practices related to data collection and processing that have recently emerged as influential factors in the ways that popular music is produced, distributed and consumed. By focusing on a set of findings about the way people reflect on their engagement with music within the Harkive space, this thesis engages practically and critically with these new conditions. Simultaneously, the research explores how the systems of data collection and analysis that facilitate this are technologically complex, subject to rapid change, and often hidden behind commercial and legal firewalls, making the study of them particularly difficult. This then enables us to explore how the use of digital, data and Internet technologies by many people during the course of their everyday lives is providing scholars with new opportunities and methods for undertaking research in the humanities, and how this in turn is leading to questions about the role of the researcher in popular music studies, and how the discipline may take into account the new technologies and practices that have so changed the field. Ultimately, the thesis makes the argument that a greater practical understanding and critical engagement with digital, data and Internet technologies is essential, both for music consumers and popular music scholars, and demonstrates how this work represents a significant contribution to this task

Kenyon Collegian - December 6, 1979

https://digital.kenyon.edu/collegian/2031/thumbnail.jp

Proceedings, MSVSCC 2014

Proceedings of the 8th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 17, 2014 at VMASC in Suffolk, Virginia

Accurate sound synthesis of 3D object collisions in interactive virtual scenarios

Questa tesi affronta lo studio di algoritmi efficienti per la sintesi di suoni risultanti dalla collisione di oggetti generici, partendo da una descrizione fisica del problema. L'obiettivo della ricerca e' lo sviluppo di strumenti in grado di aumentare l'accuratezza del feedback uditivo in ambienti di realta' virtuale attraverso un approccio basato sulla fisica, senza il bisogno quindi di far riferimento a suoni pre-registrati. Data la loro versatilita' nel trattare geometrie complesse, i metodi agli elementi finiti (FEM) sono stati scelti per la discretizzazione spaziale di generici risonatori tridimensionali. Le risultanti equazioni discrete sono riarrangiate in modo da disaccoppiare i modi normali del sistema tramite l'utilizzo di tecniche di Analisi e Sintesi Modale. Queste tecniche, infatti, portano convenientemente ad algoritmi computazionalmente efficienti per la sintesi del suono. Implementazioni di esempio di tali algoritmi sono state sviluppate facendo uso solo di software open-source: questo materiale a corredo della tesi permette una migliore riproducibilita' dei risultati di questa tesi da parte di ricercatori aventi una preparazione nel campo della sintesi audio. I risultati originali presenti in questo lavoro includono: i tecniche efficienti basate sulla fisica che aiutano l'implementazione in tempo reale di algoritmi di sintesi del suono su hardware comune; ii un metodo per la gestione efficiente dei dati provenienti da analisi FEM che, assieme ad un modello espressivo per la dissipazione, permette di calcolare l'informazione caratterizzante un oggetto risonante e salvarla in una struttura dati compatta iii una trasformazione nel dominio discreto del tempo su due diverse rappresentazioni nello spazio degli stati di filtri digitali del secondo ordine, che permette il calcolo esatto di variabili derivate come la velocita' e l'energia di un risonatore anche quando semplici realizzazioni a soli poli sono impiegate i un'efficiente realizzazione multirate di un banco parallelo di risonatori, derivata usando una suddivisione con Quadrature-Mirror-Filters (QMF). Confrontata con lavori simili presenti in letteratura, questa realizzazione permette l'uso di eccitazione nonlineare in feedback per un banco di risonatori in multirate: l'idea chiave consiste nello svolgere un cambio di stato adattivo nel banco di risonatori, muovendo i risonatori dalla frequenza di campionamento elevata, usata per il processamento della fase transiente, ad un insieme di sottofrequenze ridotte usate durante l'evoluzione in stato libero del sistema.This thesis investigates efficient algorithms for the synthesis of sounds produced by colliding objects, starting from a physical description of the problem. The objective of this investigation is to provide tools capable of increasing the accuracy of the synthetic auditory feedback in virtual environments through a physics-based approach, hence without the need of pre-recorded sounds. Due to their versatility in dealing with complex geometries, Finite Element Methods (FEM) are chosen for the space-domain discretization of generic three-dimensional resonators. The resulting state-space representations are rearranged so as to decouple the normal modes in the corresponding equations, through the use of Modal Analysis/Synthesis techniques. Such techniques, in fact, conveniently lead to computationally efficient sound synthesis algorithms. The whole mathematical treatment develops until deriving such algorithms. Finally, implementation examples are provided which rely only on open-source software: this companion material guarantees the reproducibility of the results, and can be handled without much effort by most researchers having a background in sound processing. The original results presented in this work include: i efficient physics-based techniques that help implement real-time sound synthesis algorithms on common hardware; ii a method for the efficient management of FEM data which, by working together with an expressive damping model, allows to pre-compute the information characterizing a resonating object and then to store it in a compact data structure; iii a time-domain transformation of the state-space representation of second-order digital filters, allowing for the exact computation of dependent variables such as resonator velocity and energy, even when simple all-pole realizations are used; iv an efficient multirate realization of a parallel bank of resonators, which is derived using a Quadrature-Mirror-Filters (QMF) subdivision. Compared to similar works previously proposed in the literature, this realization allows for the nonlinear feedback excitation of a multirate filter bank: the key idea is to perform an adaptive state change in the resonator bank, by switching the sampling rate of the resonators from a common highest value, used while processing the initial transient of the signals at full bandwidth, to a set of lower values in ways to enable a multirate realization of the same bank during the steady state evolution of the signals

Deep Model for Improved Operator Function State Assessment

A deep learning framework is presented for engagement assessment using EEG signals. Deep learning is a recently developed machine learning technique and has been applied to many applications. In this paper, we proposed a deep learning strategy for operator function state (OFS) assessment. Fifteen pilots participated in a flight simulation from Seattle to Chicago. During the four-hour simulation, EEG signals were recorded for each pilot. We labeled 20- minute data as engaged and disengaged to fine-tune the deep network and utilized the remaining vast amount of unlabeled data to initialize the network. The trained deep network was then used to assess if a pilot was engaged during the four-hour simulation