The design and development of music eScape: A new iPhone mood management music App

The physical, emotional, educational and social developmental challenges of adolescence can be associated with high levels of emotional vulnerability. Thus, the development of effective emotion-regulation strategies is crucial during this time period. Young people commonly use music to identify, express and regulate their emotions. Modern mobile technology provides an engaging, easily accessible means of assisting young people through music. A systematic contextual review identified 20 iPhone applications addressing emotions through music and two independent raters, using the Mobile App Rating Scale (MARS), evaluated the quality of the apps. Their characteristics, key features and overall quality will be presented. Three participatory design workshops (N=13, 6 males, 7 females; age 15-25) were conducted to explore young people’s use of music to enhance wellbeing. Young people were also asked to trial existing mood and music apps and to conceptualise their ultimate mood targeting music application. A thematic analysis of the participatory design workshops content identified the following music affect-regulation strategies: relationship building, modifying cognitions, modifying emotions, and immersing in emotions. The application of the key learnings from the mobile app review and participatory design workshops and the design and development of the music eScape app were presented and implications for future research was discussed.

Young people's uses of music for well-being

The period between 15 and 25 years is characterised by much personal change and is the peak age of onset of mental health problems. This prompts an interest in everyday strategies that young people might use to support their well-being. Music use is the preferred leisure activity among young people yet little is known about how music is linked to well-being in this population. This study aimed to develop and test a model of the relationships between young people’s use of music and their well-being, drawing on theories from the music psychology and clinical psychology fields. A qualitative analysis of transcripts from focus groups with 11 participants aged 15–25 years revealed four ways in which music listening links with well-being: relationship building, modifying emotions, modifying cognitions and emotional immersion. These linking variables were operationalised using questionnaire scores and tested on a new sample of 107 young people. Results of a multiple mediation analysis revealed that music listening was significantly related to all four linking variables, but not directly related to well-being as measured by the Mental Health Continuum. Nevertheless, the four linking variables indirectly mediated the effect of music listening on social wellbeing. The findings are consistent with earlier research on the role of music in emotion regulation and social connection although there are clearly other factors involved in determining young peoples’ well-being. These findings will help inform music-based interventions for young people.

Music in the prevention and treatment of substance misuse

Issues Research shows that young people at risk of developing a substance use disorder often use substances to deal with problems, particularly relationship problems and emotional problems. Music listening is a widely available and engaging activity that may help young people address these problem areas. This study was part of a larger project to develop a phone app for young people in which they use music for emotional wellbeing. Approach Three focus groups with young people aged 15–25 years were conducted and the transcripts were analysed by three of the authors using a thematic analysis procedure (Braun & Clarke, 2006). Key Findings: Young people used music in four main ways to achieve wellbeing: relationship building through sharing music; cre- ating an ambience using music; using music to experience an emotion more fully; and using music to modify an emotion. Several mecha- nisms by which music achieved these functions were identified. Par- ticipants also articulated specific times when they would not use music and why. Discussion and Conclusions The information from these focus groups provides many avenues for the development of the app and for understanding how music listening helps young people to achieve wellbeing. These ideas can readily be used with young people at risk of developing substance use problems as it gives them an engaging and low cost alternative for managing their emotions and building relationships.

Maintaining our rage: Inside Australia's longest-running music video program

This research presents an insider's account of rage, Australia's longest-running music video program. The research's significance is that there has been scarce scholarly analysis of this idiosyncratic ABC program, despite its longevity and uniqueness. The thesis takes a reflective and reflexive narrative journey across rage's decades, presenting the accounts of the program makers, aided by the perspective of an embedded researcher, the program's former Series Producer. This work addresses the rage research gap and contributes to the scholarly discussion on music video and its contexts, the ABC, public service broadcasting, creative labour, and the cultural sense-making of television producers.

Mediated music makers : Constructing author images in popular music

The subject of the thesis is the mediated construction of author images in popular music. In the study, the construction of images is treated as a process in which artists, the media and the members of the audience participate. The notions of presented, mediated and compiled author images are used in explaining the mediation process and the various authorial roles of the agents involved. In order to explore the issue more closely, I analyse the author images of a group of popular music artists representing the genres of rock, pop and electronic dance music. The analysed material consists mostly of written media texts through which the artists authorial roles and creative responsibilities are discussed. Theoretically speaking, the starting points for the examination lie in cultural studies and discourse analysis. Even though author images may be conceived as intertextual constructions, the artist is usually presented as a recognizable figure whose purpose is to give the music its public face. This study does not, then, deal with musical authors as such, but rather with their public images and mediated constructions. Because of the author-based functioning of popular music culture and the idea of the artist s individual creative power, the collective and social processes involved in the making of popular music are often superseded by the belief in a single, originating authorship. In addition to the collective practices of music making, the roles of the media and the marketing machinery complicate attempts to clarify the sharing of authorial contributions. As the case studies demonstrate, the differences between the examined author images are connected with a number of themes ranging from issues of auteurism and stardom to the use of masked imagery and the blending of authorial voices. Also the emergence of new music technologies has affected not only the ways in which music is made, but also how the artist s authorial status and artistic identity is understood. In the study at hand, the author images of auteurs, stars, DJs and sampling artists are discussed alongside such varied topics as collective authorship, evaluative hierarchies, visual promotion and generic conventions. Taken altogether, the examined case studies shed light on the functioning of popular music culture and the ways in which musical authorship is (re)defined.

The Development of the Concept of Music Education in Estonian Kindergartens, 1905-2008 : a Historical–Critical Overview

The dissertation focuses on the development of music education in Estonian kindergartens and the factors influencing it, analysed in the historical perspective relying on post-positivist paradigm. The study is based on the factors and subjects’ views on kindergarten music education from 1905 to 2008, recorded in written sources or ascertained by means of questionnaire and interview. The dissertation deals with music’s functions, music education in retrospective, factors influencing child’s musical aptitude and development and teacher’s role in it through the prism of history. The formation of Estonian kindergarten music education and the phenomenon of its development have been researched by stages: the first manifestations of music in kindergarten in 1905 - 1940; the formation of the concept of music education in 1941 - 1967 and the application of a unified system in 1968 - 1990. The work also outlines innovative trends in music education at the end of the last millennium and the beginning of this century, in 1991 - 2008. The study relies on a combined design and an analysis of historical archival material and empirical data. The empirical part of the study is based on the questionnaire (n=183) and interviews (n=18) carried out with kindergarten music teachers. The data has been analysed using both qualitative and quantitative methods. The subject of the research is the content and activity types of kindergarten music education and the role of music teacher in their implementation. The study confirmed that fundamental changes took place in Estonian kindergarten music education due to the change in political power in the 1940s. Following the example of the Soviet system of education, music in kindergarten became an independent music educational orientation and the position of a professionally trained music teacher was established (1947). It was also confirmed that in the newly independent Estonian Republic under the influence of innovative trends a new paradigm of music education arose from the traditional singing-centred education towards the more balanced use of music activity types (attaching importance to the child-centred approach, an increase in the number and variety of activity types). The most important conclusions made in the dissertation are that there has been improvement and development deriving from contemporary trends in the clear concept that has evolved in Estonian kindergarten music education over a century; professionally trained music teachers have had a crucial role in shaping it; and kindergarten music education is firmly positioned as a part of preschool education in Estonian system of education. Key words: early childhood music education, history of music education, kindergarten music education, early childhood music teachers

A statistical analysis of audience sound absorption (A)

The absorption produced by the audience in concert halls is considered a random variable. Beranek's proposal [L. L. Beranek, Music, Acoustics and Architecture (Wiley, New York, 1962), p. 543] that audience absorption is proportional to the area they occupy and not to their number is subjected to a statistical hypothesis test. A two variable linear regression model of the absorption with audience area and residual area as regressor variables is postulated for concert halls without added absorptive materials. Since Beranek's contention amounts to the statement that audience absorption is independent of the seating density, the test of the hypothesis lies in categorizing halls by seating density and examining for significant differences among slopes of regression planes of the different categories. Such a test shows that Beranek's hypothesis can be accepted. It is also shown that the audience area is a better predictor of the absorption than the audience number. The absorption coefficients and their 95% confidence limits are given for the audience and residual areas. A critique of the regression model is presented.

Weighted subspace methods and spatial smoothing: analysis and comparison

The effect of using a spatially smoothed forward-backward covariance matrix on the performance of weighted eigen-based state space methods/ESPRIT, and weighted MUSIC for direction-of-arrival (DOA) estimation is analyzed. Expressions for the mean-squared error in the estimates of the signal zeros and the DOA estimates, along with some general properties of the estimates and optimal weighting matrices, are derived. A key result is that optimally weighted MUSIC and weighted state-space methods/ESPRIT have identical asymptotic performance. Moreover, by properly choosing the number of subarrays, the performance of unweighted state space methods can be significantly improved. It is also shown that the mean-squared error in the DOA estimates is independent of the exact distribution of the source amplitudes. This results in a unified framework for dealing with DOA estimation using a uniformly spaced linear sensor array and the time series frequency estimation problems.

Performance analysis of a modified spatial smoothing technique for direction estimation

The statistical performance analysis of ESPRIT, root-MUSIC, minimum-norm methods for direction estimation, due to finite data perturbations, using the modified spatially smoothed covariance matrix, is developed. Expressions for the mean-squared error in the direction estimates are derived based on a common framework. Based on the analysis, the use of the modified smoothed covariance matrix improves the performance of the methods when the sources are fully correlated. Also, the performance is better even when the number of subarrays is large unlike in the case of the conventionally smoothed covariance matrix. However, the performance for uncorrelated sources deteriorates due to an artificial correlation introduced by the modified smoothing. The theoretical expressions are validated using extensive simulations. (C) 1999 Elsevier Science B.V. All rights reserved.

A transient detection algorithm for audio using iterative analysis of STFT

We propose an iterative algorithm to detect transient segments in audio signals. Short time Fourier transform(STFT) is used to detect rapid local changes in the audio signal. The algorithm has two steps that iteratively - (a) calculate a function of the STFT and (b) build a transient signal. A dynamic thresholding scheme is used to locate the potential positions of transients in the signal. The iterative procedure ensures that genuine transients are built up while the localised spectral noise are suppressed by using an energy criterion. The extracted transient signal is later compared to a ground truth dataset. The algorithm performed well on two databases. On the EBU-SQAM database of monophonic sounds, the algorithm achieved an F-measure of 90% while on our database of polyphonic audio an F-measure of 91% was achieved. This technique is being used as a preprocessing step for a tempo analysis algorithm and a TSR (Transients + Sines + Residue) decomposition scheme.

Music and symbolic dynamics: the science behind an art

Music signals comprise of atomic notes drawn from a musical scale. The creation of musical sequences often involves splicing the notes in a constrained way resulting in aesthetically appealing patterns. We develop an approach for music signal representation based on symbolic dynamics by translating the lexicographic rules over a musical scale to constraints on a Markov chain. This source representation is useful for machine based music synthesis, in a way, similar to a musician producing original music. In order to mathematically quantify user listening experience, we study the correlation between the max-entropic rate of a musical scale and the subjective aesthetic component. We present our analysis with examples from the south Indian classical music system.

Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation

The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.

Transceiver designs and analysis for LTI, LTV and broadcast channels - new matrix decompositions and majorization theory

Signal processing techniques play important roles in the design of digital communication systems. These include information manipulation, transmitter signal processing, channel estimation, channel equalization and receiver signal processing. By interacting with communication theory and system implementing technologies, signal processing specialists develop efficient schemes for various communication problems by wisely exploiting various mathematical tools such as analysis, probability theory, matrix theory, optimization theory, and many others. In recent years, researchers realized that multiple-input multiple-output (MIMO) channel models are applicable to a wide range of different physical communications channels. Using the elegant matrix-vector notations, many MIMO transceiver (including the precoder and equalizer) design problems can be solved by matrix and optimization theory. Furthermore, the researchers showed that the majorization theory and matrix decompositions, such as singular value decomposition (SVD), geometric mean decomposition (GMD) and generalized triangular decomposition (GTD), provide unified frameworks for solving many of the point-to-point MIMO transceiver design problems.

In this thesis, we consider the transceiver design problems for linear time invariant (LTI) flat MIMO channels, linear time-varying narrowband MIMO channels, flat MIMO broadcast channels, and doubly selective scalar channels. Additionally, the channel estimation problem is also considered. The main contributions of this dissertation are the development of new matrix decompositions, and the uses of the matrix decompositions and majorization theory toward the practical transmit-receive scheme designs for transceiver optimization problems. Elegant solutions are obtained, novel transceiver structures are developed, ingenious algorithms are proposed, and performance analyses are derived.

The first part of the thesis focuses on transceiver design with LTI flat MIMO channels. We propose a novel matrix decomposition which decomposes a complex matrix as a product of several sets of semi-unitary matrices and upper triangular matrices in an iterative manner. The complexity of the new decomposition, generalized geometric mean decomposition (GGMD), is always less than or equal to that of geometric mean decomposition (GMD). The optimal GGMD parameters which yield the minimal complexity are derived. Based on the channel state information (CSI) at both the transmitter (CSIT) and receiver (CSIR), GGMD is used to design a butterfly structured decision feedback equalizer (DFE) MIMO transceiver which achieves the minimum average mean square error (MSE) under the total transmit power constraint. A novel iterative receiving detection algorithm for the specific receiver is also proposed. For the application to cyclic prefix (CP) systems in which the SVD of the equivalent channel matrix can be easily computed, the proposed GGMD transceiver has K/log_2(K) times complexity advantage over the GMD transceiver, where K is the number of data symbols per data block and is a power of 2. The performance analysis shows that the GGMD DFE transceiver can convert a MIMO channel into a set of parallel subchannels with the same bias and signal to interference plus noise ratios (SINRs). Hence, the average bit rate error (BER) is automatically minimized without the need for bit allocation. Moreover, the proposed transceiver can achieve the channel capacity simply by applying independent scalar Gaussian codes of the same rate at subchannels.

In the second part of the thesis, we focus on MIMO transceiver design for slowly time-varying MIMO channels with zero-forcing or MMSE criterion. Even though the GGMD/GMD DFE transceivers work for slowly time-varying MIMO channels by exploiting the instantaneous CSI at both ends, their performance is by no means optimal since the temporal diversity of the time-varying channels is not exploited. Based on the GTD, we develop space-time GTD (ST-GTD) for the decomposition of linear time-varying flat MIMO channels. Under the assumption that CSIT, CSIR and channel prediction are available, by using the proposed ST-GTD, we develop space-time geometric mean decomposition (ST-GMD) DFE transceivers under the zero-forcing or MMSE criterion. Under perfect channel prediction, the new system minimizes both the average MSE at the detector in each space-time (ST) block (which consists of several coherence blocks), and the average per ST-block BER in the moderate high SNR region. Moreover, the ST-GMD DFE transceiver designed under an MMSE criterion maximizes Gaussian mutual information over the equivalent channel seen by each ST-block. In general, the newly proposed transceivers perform better than the GGMD-based systems since the super-imposed temporal precoder is able to exploit the temporal diversity of time-varying channels. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD DFE transceiver is also proposed.

The third part of the thesis considers two quality of service (QoS) transceiver design problems for flat MIMO broadcast channels. The first one is the power minimization problem (min-power) with a total bitrate constraint and per-stream BER constraints. The second problem is the rate maximization problem (max-rate) with a total transmit power constraint and per-stream BER constraints. Exploiting a particular class of joint triangularization (JT), we are able to jointly optimize the bit allocation and the broadcast DFE transceiver for the min-power and max-rate problems. The resulting optimal designs are called the minimum power JT broadcast DFE transceiver (MPJT) and maximum rate JT broadcast DFE transceiver (MRJT), respectively. In addition to the optimal designs, two suboptimal designs based on QR decomposition are proposed. They are realizable for arbitrary number of users.

Finally, we investigate the design of a discrete Fourier transform (DFT) modulated filterbank transceiver (DFT-FBT) with LTV scalar channels. For both cases with known LTV channels and unknown wide sense stationary uncorrelated scattering (WSSUS) statistical channels, we show how to optimize the transmitting and receiving prototypes of a DFT-FBT such that the SINR at the receiver is maximized. Also, a novel pilot-aided subspace channel estimation algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) systems with quasi-stationary multi-path Rayleigh fading channels. Using the concept of a difference co-array, the new technique can construct M^2 co-pilots from M physical pilot tones with alternating pilot placement. Subspace methods, such as MUSIC and ESPRIT, can be used to estimate the multipath delays and the number of identifiable paths is up to O(M^2), theoretically. With the delay information, a MMSE estimator for frequency response is derived. It is shown through simulations that the proposed method outperforms the conventional subspace channel estimator when the number of multipaths is greater than or equal to the number of physical pilots minus one.