945 resultados para Music Recommender Systems
Resumo:
This study aimed to examine the effects on driving, usability and subjective workload of performing music selection tasks using a touch screen interface. Additionally, to explore whether the provision of visual and/or auditory feedback offers any performance and usability benefits. Thirty participants performed music selection tasks with a touch screen interface while driving. The interface provided four forms of feedback: no feedback, auditory feedback, visual feedback, and a combination of auditory and visual feedback. Performance on the music selection tasks significantly increased subjective workload and degraded performance on a range of driving measures including lane keeping variation and number of lane excursions. The provision of any form of feedback on the touch screen interface did not significantly affect driving performance, usability or subjective workload, but was preferred by users over no feedback. Overall, the results suggest that touch screens may not be a suitable input device for navigating scrollable lists.
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This article examines the design of ePortfolios for music postgraduate students utilizing a practice-led design iterative research process. It is suggested that the availability of Web 2.0 technologies such as blogs and social network software potentially provide creative artist with an opportunity to engage in a dialogue about art with artefacts of the artist products and processes present in that discussion. The design process applied Software Development as Research (SoDaR) methodology to simultaneously develop design and pedagogy. The approach to designing ePortfolio systems applied four theoretical protocols to examine the use of digitized artefacts to enable a dynamic and inclusive dialogue around representations of the students work. A negative case analysis identified a disjuncture between university access and control policy, and the relative openness of Web2.0 systems outside the institution that led to the design of an integrated model of ePortfolio.
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Family-centred and early intervention and prevention programs are a strong focus of current policy objectives within Australia, and a significant area of practice within the music therapy community. Recent shifts in the culture of policy and practice increasingly reflect ecological understandings by focussing on integrated and place-based approaches to service delivery. Further, current funding opportunities are strongly concerned with the extent to which interventions are able to reach out to highly vulnerable families that typically do not engage with services easily. Music therapy holds unique promise within these cultural shifts and thus advocates must develop a solid understanding of the concepts and related language in order to confidently engage with both funding and service systems. This paper uses an integrative review to first define and summarise current knowledge in three key areas relevant to contemporary Australian policy and practice: hard-to-reach families, home visiting as assertive outreach, and integrated or place-based service delivery. Evidence for the effectiveness of music therapy in relation to these key themes is then presented. Finally, the paper discusses the implications for the future of music therapy within the current Australian early intervention and prevention policy context and makes recommendations for moving forward on both practice and research fronts. While there is growing evidence and theory to suggest that music therapy may be uniquely efficacious in this area, greater Australian Journal of Music Therapy Vol 25, 2014 149 advocacy, documentation, research and adjustment of practices and language will further cement the position of the industry.
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Unlike the work available in many creative disciplines, musicians and dancers have the possibility of full-time, company-based employment; however, participants far outweigh the number of available positions. As a result, many graduates become ‘enforced entrepreneurs’ as they shape their work to meet personal and professional needs. This paper first explores the career projections of 58 music and dance students who were surveyed in their first week of post-secondary study. It then contrasts these findings with the reality of graduate careers as reported by five of that cohort four years later. In contrast with the students’ overwhelming focus on performance roles, the graduate cohort reported a prevalence of portfolio careers incorporating both creative and non-creative roles. The paper characterises the notion of a performing arts ‘career’ as a messy concept fraught with misunderstanding. Implications include the need to heighten students’ career awareness and position intrinsic satisfaction as a valued career concept.
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This research contributes a fully-operational approach for managing business process risk in near real-time. The approach consists of a language for defining risks on top of process models, a technique to detect such risks as they eventuate during the execution of business processes, a recommender system for making risk-informed decisions, and a technique to automatically mitigate the detected risks when they are no longer tolerable. Through the incorporation of risk management elements in all stages of the lifecycle of business processes, this work contributes to the effective integration of the fields of Business Process Management and Risk Management.
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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.
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The usual task in music information retrieval (MIR) is to find occurrences of a monophonic query pattern within a music database, which can contain both monophonic and polyphonic content. The so-called query-by-humming systems are a famous instance of content-based MIR. In such a system, the user's hummed query is converted into symbolic form to perform search operations in a similarly encoded database. The symbolic representation (e.g., textual, MIDI or vector data) is typically a quantized and simplified version of the sampled audio data, yielding to faster search algorithms and space requirements that can be met in real-life situations. In this thesis, we investigate geometric approaches to MIR. We first study some musicological properties often needed in MIR algorithms, and then give a literature review on traditional (e.g., string-matching-based) MIR algorithms and novel techniques based on geometry. We also introduce some concepts from digital image processing, namely the mathematical morphology, which we will use to develop and implement four algorithms for geometric music retrieval. The symbolic representation in the case of our algorithms is a binary 2-D image. We use various morphological pre- and post-processing operations on the query and the database images to perform template matching / pattern recognition for the images. The algorithms are basically extensions to classic image correlation and hit-or-miss transformation techniques used widely in template matching applications. They aim to be a future extension to the retrieval engine of C-BRAHMS, which is a research project of the Department of Computer Science at University of Helsinki.
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The problem of automatic melody line identification in a MIDI file plays an important role towards taking QBH systems to the next level. We present here, a novel algorithm to identify the melody line in a polyphonic MIDI file. A note pruning and track/channel ranking method is used to identify the melody line. We use results from musicology to derive certain simple heuristics for the note pruning stage. This helps in the robustness of the algorithm, by way of discarding "spurious" notes. A ranking based on the melodic information in each track/channel enables us to choose the melody line accurately. Our algorithm makes no assumption about MIDI performer specific parameters, is simple and achieves an accuracy of 97% in identifying the melody line correctly. This algorithm is currently being used by us in a QBH system built in our lab.
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This contribution suggests that it is possible to describe the transformations of musical style in an analogous way to the transformations of style in language, and also that it can be explained how the ‘musics in contact’ behave in an analogous way to the ‘languages in contact’. According to this idea, the ‘evolution’ of styles in music and in language can be identified and studied as dynamic exchanges in ecological niches. It is suggested, also, that the idiolectic-ecolectic, and acrolectic-basilectic relationships in music and language are functions of cycles in several ‘layers’ and ‘rhythms’. The presence of stylistic varieties and influences in music and in language may imply that they are part of major sign systems within a more complex ecological relationship.
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In the direction of arrival (DOA) estimation problem, we encounter both finite data and insufficient knowledge of array characterization. It is therefore important to study how subspace-based methods perform in such conditions. We analyze the finite data performance of the multiple signal classification (MUSIC) and minimum norm (min. norm) methods in the presence of sensor gain and phase errors, and derive expressions for the mean square error (MSE) in the DOA estimates. These expressions are first derived assuming an arbitrary array and then simplified for the special case of an uniform linear array with isotropic sensors. When they are further simplified for the case of finite data only and sensor errors only, they reduce to the recent results given in [9-12]. Computer simulations are used to verify the closeness between the predicted and simulated values of the MSE.
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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.
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Query-by-Example Spoken Term Detection (QbE STD) aims at retrieving data from a speech data repository given an acoustic query containing the term of interest as input. Nowadays, it has been receiving much interest due to the high volume of information stored in audio or audiovisual format. QbE STD differs from automatic speech recognition (ASR) and keyword spotting (KWS)/spoken term detection (STD) since ASR is interested in all the terms/words that appear in the speech signal and KWS/STD relies on a textual transcription of the search term to retrieve the speech data. This paper presents the systems submitted to the ALBAYZIN 2012 QbE STD evaluation held as a part of ALBAYZIN 2012 evaluation campaign within the context of the IberSPEECH 2012 Conference(a). The evaluation consists of retrieving the speech files that contain the input queries, indicating their start and end timestamps within the appropriate speech file. Evaluation is conducted on a Spanish spontaneous speech database containing a set of talks from MAVIR workshops(b), which amount at about 7 h of speech in total. We present the database metric systems submitted along with all results and some discussion. Four different research groups took part in the evaluation. Evaluation results show the difficulty of this task and the limited performance indicates there is still a lot of room for improvement. The best result is achieved by a dynamic time warping-based search over Gaussian posteriorgrams/posterior phoneme probabilities. This paper also compares the systems aiming at establishing the best technique dealing with that difficult task and looking for defining promising directions for this relatively novel task.
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Real-time adaptive music is now well-established as a popular medium, largely through its use in video game soundtracks. Commercial packages, such as fmod, make freely available the underlying technical methods for use in educational contexts, making adaptive music technologies accessible to students. Writing adaptive music, however, presents a significant learning challenge, not least because it requires a different mode of thought, and tutor and learner may have few mutual points of connection in discovering and understanding the musical drivers, relationships and structures in these works. This article discusses the creation of ‘BitBox!’, a gestural music interface designed to deconstruct and explain the component elements of adaptive composition through interactive play. The interface was displayed at the Dare Protoplay games exposition in Dundee in August 2014. The initial proof-of- concept study proved successful, suggesting possible refinements in design and a broader range of applications.
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The ability to imitate complex sounds is rare, and among birds has been found only in parrots, songbirds, and hummingbirds. Parrots exhibit the most advanced vocal mimicry among non-human animals. A few studies have noted differences in connectivity, brain position and shape in the vocal learning systems of parrots relative to songbirds and hummingbirds. However, only one parrot species, the budgerigar, has been examined and no differences in the presence of song system structures were found with other avian vocal learners. Motivated by questions of whether there are important differences in the vocal systems of parrots relative to other vocal learners, we used specialized constitutive gene expression, singing-driven gene expression, and neural connectivity tracing experiments to further characterize the song system of budgerigars and/or other parrots. We found that the parrot brain uniquely contains a song system within a song system. The parrot "core" song system is similar to the song systems of songbirds and hummingbirds, whereas the "shell" song system is unique to parrots. The core with only rudimentary shell regions were found in the New Zealand kea, representing one of the only living species at a basal divergence with all other parrots, implying that parrots evolved vocal learning systems at least 29 million years ago. Relative size differences in the core and shell regions occur among species, which we suggest could be related to species differences in vocal and cognitive abilities.