Search

Resumo Este artigo pretende propor uma interpretação de Wavelength (1967), de Michael Snow, que privilegie a noção de processo, em detrimento da noção de estrutura, que tem sido o conceito predominante na extensa fortuna crítica do filme. A hipótese aqui apresentada é a de que podemos compreender melhor a proposta e as implicações do filme contextualizando seus procedimentos no debate da música e da arte processual nos anos 1960, a partir de uma genealogia do conceito crítico de processo e do estudo comparativo entre cinema, arte e música. Abstract This paper proposes an interpretation of Wavelength (1967), by Michael Snow, that privileges the notion of process rather than the notion of structure, which has been a predominant concept in Snow’s extensive critical fortune. The hypothesis presented here is that we can better understand the proposal and implications of the film by contextualizing its procedures in the critical debate on process music and art in the 1960s, through a genealogical and comparative study.

In the modern educational process music adapts to changes of everyday life and develops in the context of modern technologies. Following the needs, interests and abilities of the preschooler, preschool teachers use music through all available means of sound reproduction, combining it with their own potential and capabilities of musical expression. This paper is the result of the growing intellectual and musical potential of a preschooler who actively engages different senses in learning music: from sound to colour. The aim is to create a computer application which facilitates music learning through learning colours. The method is determined by using the application within the Max / MSP / Jitter (Max) programming language. Max is a visual programming language whose environment is based on combining objects and applications into configurations intended for music and multimedia. The aim of the paper is overcoming the basic concepts of musical literacy through using a specific colour as a carrier of organizing the music flow. The potential of this program aimed at preschool children is that learning music in the modern educational system is understood through a compromise with the development of the demands of modern technology of which music is an integral part.

This article explores similarities between the permutational processes in sound poetry and process music, suggesting models for new music which supports audience comprehension of processual languag...

Electronic music emotion recognition technology uses computers to analyze and process music features, study the mapping relationship between music feature space and emotional space, and realize the cognitive process of the emotions expressed by music. Based on the BP neural network, this paper analyzes the emotion recognition algorithms of different electronic music signals. First, according to the organizational structure of music, a musical model was established. Then, use timbre to divide the music into a number of independent sections. Finally, the BP network algorithm is used to identify electronic music. Experiments show the effectiveness of the algorithm.

Introduction: Evidence supporting the use of music interventions to maximize arousal and awareness in adults presenting with a disorder of consciousness continues to grow. However, the brain of a child is not simply a small adult brain, and therefore adult theories are not directly translatable to the pediatric population. The present study aims to synthesize brain imaging data about the neural processing of music in children aged 0-18 years, to form a theoretical basis for music interventions with children presenting with a disorder of consciousness following acquired brain injury.Methods: We conducted a systematic review with narrative synthesis utilizing an adaptation of the methodology developed by Popay and colleagues. Following the development of the narrative that answered the central question “what does brain imaging data reveal about the receptive processing of music in children?”, discussion was centered around the clinical implications of music therapy with children following acquired brain injury.Results: The narrative synthesis included 46 studies that utilized EEG, MEG, fMRI, and fNIRS scanning techniques in children aged 0-18 years. From birth, musical stimuli elicit distinct but immature electrical responses, with components of the auditory evoked response having longer latencies and variable amplitudes compared to their adult counterparts. Hemodynamic responses are observed throughout cortical and subcortical structures however cortical immaturity impacts musical processing and the localization of function in infants and young children. The processing of complex musical stimuli continues to mature into late adolescence.Conclusion: While the ability to process fundamental musical elements is present from birth, infants and children process music more slowly and utilize different cortical areas compared to adults. Brain injury in childhood occurs in a period of rapid development and the ability to process music following brain injury will likely depend on pre-morbid musical processing. Further, a significant brain injury may disrupt the developmental trajectory of complex music processing. However, complex music processing may emerge earlier than comparative language processing, and occur throughout a more global circuitry.

Professor Philip Ewell shocked the music theory world at the Society for Music Theory conference in 2019 when he charged that American music theory was systematically racist. In particular, he used long-deceased German theorist, Henrich Schenker, "as an exemplar of that flawed world, a ‘virulent racist' who wrote of ‘primitive' and ‘inferior' races — views, he argued, that suffused his theories of music." Furthermore, he accused "generations of Schenker scholars of trying to ‘whitewash' the theorist in an act of ‘colorblind racism.'" In this paper, I will examine whether Ewell’s arguments are consistent with science, in particular, cognitive psychology. Based on this examination, I conclude that Ewell’s theories are inconsistent with well-established concepts of human behavior and how the mind works, as well as how humans perceive and process music. Part II of this paper will present Ewell’s arguments about Schenker and music theory. Part III will show that Ewell’s “white racial framework,” a type of social constructionist argument, is faulty because the human brain does not operate in a manner that is consistent with social constructionism. Rather, the foundation of human thinking is rooted in biology. Part IV will debunk Ewell’s argument about the myth of neutrality by showing that music is to a significant extent universal. Part V will deal with other problems in Ewell’s arguments, particularly his treatment of people of color and whites as a monoliths and his superficial analysis of statistics due to his correlation/causation fallacy and his lack of context for his analysis. Part VI will critique Ewell’s argument that Schenker’s theory is racist because he was personally racist. First, it will attack the false analogy between personal racism and hierarchy in music. Equally importantly, it will demonstrate that Schenker’s theories reflect how the human mind perceives and processes music. This paper will end by discussing the dangers of using faulty theories (theory-induced blindness).

The author considers the metaphysics of Aristotle in its significance for the aesthetics and the philosophy of music, where the music is, first of all, by its nature is presented as a substance (essence, consisting in movement, rhythm, among other things, the divine mind) and, secondly, as a becoming shape musical art, the value of human interaction with the world. In the author’s interpretation of the Aristotelian doctrine of the essence, the music is becoming substantialistically musical being. In the making of the musical form the laws of the logos, Mind, creation. Concepts: substance (essence), matter and form, entelechy, energy - are considered in the context of aesthetics and musical art. The author draws attention to the fact that the issue of music as an art form in the world of human existence, Aristotle was interested in music for the purpose of man, where he shared a professional work and making music, you need to nurture. Noting its purpose, according to the philosopher said, pleasure, recreation, virtue, purification of the soul, it was found that the ability of music to influence the moral aspect of the soul remained for him an open problem. Aristotle’s metaphysics approved idea of music as a musical form and substance as a process music as a means of value of human interaction with the world, which makes the belief in the stability of the laws of becoming of musical forms.

Musical training causes structural and functional changes in the brain due to its sensory-motor demands. This leads to differences in how musicians perceive and process music as compared to non-musicians, thereby providing insights into brain adaptations and plasticity. Correlational studies and network analysis investigations have indicated the presence of large-scale brain networks involved in the processing of music and have highlighted differences between musicians and non-musicians. However, studies on functional connectivity in the brain during music listening tasks have thus far focused solely on static network analysis. Dynamic Functional Connectivity (DFC) studies have lately been found useful in unearthing meaningful, time-varying functional connectivity information in both resting-state and task-based experimental settings. In this study, we examine DFC in the fMRI obtained from two groups of participants, 18 musicians and 18 non-musicians, while they listened to a musical stimulus in a naturalistic setting. We utilize spatial Group Independent Component Analysis (ICA), sliding time window correlations, and a deterministic agglomerative clustering of windowed correlation matrices to identify quasi-stable Functional Connectivity (FC) states in the two groups. To compute cluster centroids that represent FC states, we devise and present a method that primarily utilizes windowed correlation matrices occurring repeatedly over time and across participants, while excluding matrices corresponding to spontaneous fluctuations. Preliminary analysis indicate states with greater visuo-sensorimotor integration in musicians, larger presence of DMN states in non-musicians, and variability in states found in musicians due to differences in training and prior experiences. peerReviewed

We present a method for emotional musification that utilizes the musical game MUSE. We take advantage of the strong links between music and emotion to represent emotions as music. While we provide a prototype for measuring emotion using facial expression and physiological signals our sonification is not dependent on this. Rather we identify states within MUSE that elicit certain emotions and map those onto the arousal and valence spatial representation of emotion. In this way our efforts are compatible with emotion detection methods which can be mapped to arousal and valence. Because MUSE is based on states and state transitions we gain the ability to transition seamlessly from one state to another as new emotions are detected thus avoiding abrupt changes between music types.

Arvo Pärt's music has received little attention from theoretical scholars, in part, because it is often labelled as minimalist or process music. This is due primarily to his use of limited sets of musical materials and predetermined repetitive melodic and rhythmic procedures. In this sense, it is implied that authorial decisions play little role in the compositional process of his music. In addition, the confluences of multiple M-voice/T-voice pairings, which create a rich array of harmonically non-functional chord progressions, do not lend themselves to traditional approaches to musical analysis, thus acting as a further deterrent to analysts and theorists. This investigation postulates that the presence of the 'composer's hand' is much more significant in Pärt's music than has been previously realised by those who label his music as minimalist or process music; and by engaging in a multimodal methodology, this thesis demonstrates that Pärt's music does, in fact, respond to post-tonal analytical approaches. It also shows that a non-traditional application of post-tonal analytical techniques can yield valuable and productive insights into Pärt's compositional system, and that there is actually much for theorists and analysts to discover in his music. The approach to the investigation is based on drawing from and combining several post-tonal analytical methods, any one of which would be insufficient on its own, given the uniqueness of Pärt's sound world and the fact that such approaches have been developed to enlighten very different repertoires. The methodology incorporates the following post-tonal analytical methods: descriptions of the 'musical fabric' of each work; a detailed analysis of how each composition appears to have been constructed; new approaches to visualising the relationships between the pitch classes of particular works; and mappings of each work's pitch-class and interval-vector content. This investigation demonstrates, through multimodal analysis of six selected string orchestral works by the composer, that hidden beneath the seemingly 'minimal' surface layers of Pärt's music are carefully crafted musical constructions that result from intersecting procedures and multifaceted rules, as well as what appear to be intentional exceptions to those rules - thus revealing the composer's hand. An awareness of these hidden constructions and the careful craftsmanship that went into their creation can provide the informed listener with the critical foundation from which the aesthetic value of Pärt's music can be assessed and appreciated.

Data mining tasks such as music indexing, information retrieval, and similarity search, require an understanding of how listeners process music internally. Many algorithms for automatically analyzing the structure of recorded music assume that a large change in one or another musical feature suggests a section boundary. However, this assumption has not been tested: while our understanding of how listeners segment melodies has advanced greatly in the past decades, little is known about how this process works with more complex, full-textured pieces of music, or how stable this process is across genres. Knowing how these factors affect how boundaries are perceived will help researchers to judge the viability of algorithmic approaches with different corpora of music. We present a statistical analysis of a large corpus of recordings whose formal structure was annotated by expert listeners. We find that the acoustic properties of boundaries in these recordings corroborate findings of previous perceptual experiments. Nearly all boundaries correspond to peaks in novelty functions, which measure the rate of change of a musical feature at a particular time scale. Moreover, most of these boundaries match peaks in novelty for several features at several time scales. We observe that the boundary-novelty relationship can vary with listener, time scale, genre, and musical feature. Finally, we show that a boundary profile derived from a collection of novelty functions correlates with the estimated salience of boundaries indicated by listeners.

Sensitivity for music is a diffuse property of the human brain. When we listen to music, the entire brain is active. In particular, the auditory cortex has connections to the frontal lobe of the brain where many of our capabilities for abstraction and inference are located. A widely accepted idea (although it is unproven) is that humans have an inborn capacity to process music. David Huron highlighted the adaptive advantage of having a mind able to recognize sound patterns and to extract complex significances from a heterogeneous flux of sounds arriving from the environment (Huron, 1991). Probably our ability to recognize complex sound patterns is one of the results of natural evolution of humans' cognitive capabilities (Ball, 2010). These concepts suggest the following idea: we could use complex sounds (and music in particular), and not only images, for geophysical data analysis, interpretation, and integration. An advantage to this could derive from the fact that sounds have many physical, perceptive, psychological, and cultural “dimensions”: this implies an expanded range of possibilities for analyzing and interpreting geophysical signals transformed into sounds. […] Human sensitivity for music (and for sounds in general) is nowadays supported by advanced technology and by many formats and informatics' protocols used in digital music (such as wav, mp3, MIDI). These allow easy sound manipulation, analysis, and integration. In particular, the MIDI protocol links heterogeneous information through multiple types of media. There is an additional reason why geophysical data analysis/interpretation could be performed in the domain of sounds and music: the nature of several types of geophysical signals, like seismic data, is closer to the physics of sounds than to the physics of images. These ideas have been investigated (partially) by other authors (Benioff, 1953; Speeth, 1961; Hayward, 1994; Kilb et al., 2012; Peng et al., 2012). In this article, I expand them by proposing a new approach based on exploring new interesting connections between geosciences and the most recent technological innovations in the domain of digital music.

Music structural analysis tasks have an important position in the field of Music information retrieval which require an understanding of how humans process music internally, such as music indexing, music summarization, and similarity analysis. Many schemes have been proposed to analyze the structure of recorded music, however they usually use single feature to detect boundaries of songs and the results are not satisfactory. In this paper, we present a method which is based on novelty detection and combines multiple features to the task of music boundaries detection. We extract peaks of novelty function derived from various features as potential boundaries, then eliminate non-boundaries from potential boundaries derived from distinct feature sets. Three types of features, including intensity, timbre, and harmony are employed to represent the characteristics of a music clip. On our testing database composed of 175 entire songs, the best accuracy of boundary detection with tolerance ±3 seconds achieves up to 65.7%.

As an important way of music retrieval, Query-By-Humming has gained wide attention because of its effectiveness and convenience. This paper proposes a novel Top-K similarity search technique, which provides fast retrieval for Query-By-Humming. We propose a distance function MDTW for multi-dimensional sequence matching as well as a subsequence matching method \(MDTW_{sub}\). We show that the proposed method is highly applicable to music retrieval. In our paper, music pieces are represented by 2-dimensional time series, where each dimension holds information about the pitch or duration of each note, respectively. In order to improve the efficiency, we utilize inverted lists and q-gram technique to process music database, and utilize q-chunk technique to process hummed piece. Then, we calculate the MDTW distances between hummed q-chunks and music q-grams, and we can get the candidate music and their sensitive data areas. We proposes TopK-Brute and TopK-LB Algorithm to search the Top-K songs. The experimental results demonstrate both the efficiency and effectiveness of our approach.

A number of evolutionary theories assume that music and language have a common origin as an emotional protolanguage that remains evident in overlapping functions and shared neural circuitry. The most basic prediction of this hypothesis is that sensitivity to emotion in speech prosody derives from the capacity to process music. We examined sensitivity to emotion in speech prosody in a sample of individuals with congenital amusia, a neurodevelopmental disorder characterized by deficits in processing acoustic and structural attributes of music. Twelve individuals with congenital amusia and 12 matched control participants judged the emotional expressions of 96 spoken phrases. Phrases were semantically neutral but prosodic cues (tone of voice) communicated each of six emotional states: happy, tender, afraid, irritated, sad, and no emotion. Congenitally amusic individuals were significantly worse than matched controls at decoding emotional prosody, with decoding rates for some emotions up to 20% lower than that of matched controls. They also reported difficulty understanding emotional prosody in their daily lives, suggesting some awareness of this deficit. The findings support speculations that music and language share mechanisms that trigger emotional responses to acoustic attributes, as predicted by theories that propose a common evolutionary link between these domains.

Query by Singing/Humming (QBSH) is a most natural way for music search. A music search system can help music finders search songs by matching a part of melody by singing or humming. Many music information retrieval techniques have been developed to carry out music search for years. On the other hand, thanks to the rapid growth of mobile wireless Internet technologies this decade, music search applications can be implemented on hand-carried devices, such as cellular phones, to conduct music search anytime and anywhere via any available networks, such as Wi-Fi, UMTS, WiMAX to the emerging 3GPP-LTE networks. In the past, little studies had ever been revealed about how to design and implement a lightweight music search engine over a fixed or mobile Internet. In this article, we aim to elaborate a practical skeleton of developing a simple music search engine over fixed or mobile networks--a Fixed-Mobile Convergent Music Search Engine (FMC-MUSE). FMC-MUSE can process music queries by QBSH from fixed or mobile clients and return a dataset containing the search results and meta-info back to music finders via ubiquitous networks.

there is debate about the extent of overlap between music and language processing in the brain and whether these processes are functionally independent in expert musicians. A language comprehension task and a visuospatial search task were administered to 36 expert musicians and 36 matched nonmusicians in conditions of silence and piano music played correctly and incorrectly. Musicians performed more poorly on the language comprehension task in the presence of background music compared to silence, but there was no effect of background music on the musicians' performance on the visuospatial task. In contrast, the performance of nonmusicians was not affected by music on either task. The findings challenge the view that music and language are functionally independent in expert musicians, and instead suggest that when musicians process music they recruit a network that overlaps with the network used in language processing. Additionally, musicians outperformed nonmusicians on both tasks, reflecting either a general cognitive advantage in musicians or enhancement of more specific cognitive abilities such as processing speed or executive functioning.

Research has suggested that musicians process music in the same cortical regions that adolescents process algebra. An early adolescence synaptogenesis might present a window of opportunity during middle school for music to create and strengthen enduring neural connections in those regions. Six school districts across Maryland provided scores from the 2006-2007 administrations of the Maryland Algebra/Data Analysis High School Assessment. Findings from a sample of 6,026 adolescents showed that students enrolled in formal instrumental or choral music instruction during middle school outperformed those who experienced neither of those modes of musical instruction. Significant mean differences in algebra achievement occurred between the instrumental and neither-instruction groups (13.34, p < .001) and between the choral and neither-instruction groups (3.82, p < .001). For African Americans, means significantly differed between the choral and neither-instruction groups (9.39, p < .001). The greatest mean difference between any two comparison groups occurred between the instrumental and neither-instruction groups of African Americans (18.87, p < .001).

The next step for the paradigm of embodied music cognition (EMC) is to move from building theories of (empirical) data toward building systematic explanations of organisms' capacities to process music. I argue that for the mirror neuron (MN) hypothesis to be effective when applied to music, these neurons' capacities should be proven to be nontrivially and causally connected with musical organisms as a whole. This requires, I argue, a mechanistic type of explanation.

Critiques of formalist modes of musical analysis resemble critiques of certain types of minimal music. One ironic, if not downright paradoxical aspect of this parallel is that the sharpest attacks on minimal music have come from writers sympathetic to formalism. A reconciliation of sorts has been reached by formalist admirers of minimalism, for whom the music is a staging ground for reflexive methodological critique.

Humans process music even without conscious effort according to implicit knowledge about syntactic regularities. Whether such automatic and implicit processing is modulated by veridical knowledge has remained unknown in previous neurophysiological studies. This study investigates this issue by testing whether the acquisition of veridical knowledge of a music-syntactic irregularity (acquired through supervised learning) modulates early, partly automatic, music-syntactic processes (as reflected in the early right anterior negativity, ERAN), and/or late controlled processes (as reflected in the late positive component, LPC). Excerpts of piano sonatas with syntactically regular and less regular chords were presented repeatedly (10 times) to non-musicians and amateur musicians. Participants were informed by a cue as to whether the following excerpt contained a regular or less regular chord. Results showed that the repeated exposure to several presentations of regular and less regular excerpts did not influence the ERAN elicited by less regular chords. By contrast, amplitudes of the LPC (as well as of the P3a evoked by less regular chords) decreased systematically across learning trials. These results reveal that late controlled, but not early (partly automatic), neural mechanisms of music-syntactic processing are modulated by repeated exposure to a musical piece. This article is part of a Special Issue entitled SI: Prediction and Attention.

This paper describes a real-time beat tracking system that recognizes a hierarchical beat structure comprising the quarter-note, half-note, and measure levels in real-world audio signals sampled from popular-music compact discs. Most previous beat-tracking systems dealt with MIDI signals and had difficulty in processing, in real time, audio signals containing sounds of various instruments and in tracking beats above the quarter-note level. The system described here can process music with drums and music without drums and can recognize the hierarchical beat structure by using three kinds of musical knowledge: of onset times, of chord changes, and of drum patterns. This paper also describes several applications of beat tracking, such as beat-driven real-time computer graphics and lighting control.

Existing music search engines process music as they would process text, ignoring the richness of this media. We introduce here MuMa1 (MUsic MAshup), a web application which makes the most of audio contents (the signal itself) to provide the user with new ways of browsing music. MuMa allows the user to search for particular chords sequences, to generate smart playlists and to extend its musical universe.

Neuroscientists are starting to discover how our brains process music. This involves distinct neural circuits, but a mystery remains. Why are melody, harmony and rhythm so important to us? Alison Abbott tunes in.

Existing music search engines process music as they would process text, ignoring the richness of this media. We introduce here MuMa1 (MUsic MAshup), a web application which makes the most of audio contents (the signal itself) to provide the user with new ways of browsing music. MuMa allows the user to search for particular chords sequences, to generate smart playlists and to extend its musical universe.

This paper introduces a software architecture for the representation and real-time processing of sound and music, based on Artificial Intelligence techniques. In particular, a system able to store and process music and sounds at different levels of abstraction, and to carry out plans for manipulating this material according to the user's goals is described. This system is able to generate new music pieces as well as manipulate existent ones, on the basis of given material: to this end, it provides also formal analysis capabilities on both music and sounds for extracting information useful in subsequent synthesis processes.

The organisation of the musical brain is a major focus of interest in contemporary neuroscience. This reflects the increasing sophistication of tools (especially imaging techniques) to examine brain anatomy and function in health and disease, and the recognition that music provides unique insights into a number of aspects of nonverbal brain function. The emerging picture is complex but coherent, and moves beyond older ideas of music as the province of a single brain area or hemisphere to the concept of music as a 'whole-brain' phenomenon. Music engages a distributed set of cortical modules that process different perceptual, cognitive and emotional components with varying selectivity. 'Why' rather than 'how' the brain processes music is a key challenge for the future.

Simulations of self-organizing neuronlike networks are used to demonstrate how untrained listeners might be able to sort their perceptions of dozens of diverse musical features into stable, meaningful schemata. A presentation is first made of the salient characteristics of such networks, especially the adaptive-resonance-theory (ART) networks proposed by Stephen Grossberg. Then a discussion follows of how a computer simulation of a four-level ART network - a simulation dubbed L'ART pour l'art - independently categorized musical events in Mozart's six earliest compositions. The ability of the network to abstract significant voiceleading combinations from these pieces (and in fact to detect a possible error in the New Mozart Edition) suggests that this approach holds promise for the study of how ordinary listeners process music's multidimensional complexity. In addition, the categorizations produced by the network are suggestive of alternative conceptualizations of music's hierarchical structure. a prim household, tidiness is a paramount virtue. Dishes line cupboards like soldiers on parade. Books march across shelves in close-order drill. There is a place for everything, and everything is in its place. A visitor senses

The beginning of Chapter 2 offered a sensible definition of music as temporally organized sound. In the broader sense of this definition, one could arguably state that music is not uniquely human. A number of other animals also seem to have music of some sort. Complex vocalizations can be found in many birds (Marler and Slabbekoorn 2004), as well as in mammals such as whales (Payne and McVay 1971) and bats (Behr and von Helversen 2004). In a chapter suggestively entitled ‘Zoomusicologie’ in the book Musique, Mythe, Nature ou Les Dauphins d’Arion, Mâche (1991) presents an interesting discussion on the formal sophistication of various birdcalls. Recently Holy and Guo (2005) demonstrated that the ultrasonic vocalizations that male mice produce when they encounter female mice or their pheromones have the characteristics of song. What is intriguing is that primates who are close related to humans are not as ‘musical’ as those mammals that are far more distantly related to us. This intriguing fact suggests that music might have evolved independently among various types of animals, at various degrees of sophistication. In this context, it would be perfectly plausible to suggest the notion that robots might also be able to evolve music. In order to build systems for the emergence of music one needs to establish the factors that may shape the course of musical evolution, such as physiological and cognitive factors, including models of interaction. The physiological factors comprise the sensors and actuators of interacting individuals. These involve models of the hearing system, body, limbs and so on. It may also involve models of the sensory-motor cortex and associated neural mechanisms involved in sensory-motor tasks. A discussion on the expertise for building these models is beyond the scope of this chapter; it includes fields such as Biomechanics (Zinkovsky, Sholuha and Ivanov 1996) and Biophysics (Glaser 2001). Readers are invited to consult the literature in these fields. As for the cognitive factors, the brain certainly uses different mental modules to process music and these modules have varying degrees of independence from each other. Parsons (2003) has conducted a number of brain-imaging experiments, which indicate that the neural system for processing music is widely distributed

This paper explores and compares the processes of music and analysis from the author's experience as a musician, piano teacher and analyst. It explains how the use of music improvisation in analysis (with simple percussion instruments) can powerfully enhance the dialogue between the unconscious and conscious psyche, as well as deepen the relationship between analyst and analysand. This is connected theoretically to Jung's active imagination and Winnicott's concept of play within the analytic encounter. Finally, the question is raised whether analytic trainings could do more to expose trainees to the possibility of using music within the analytic encounter. This touches on the more basic and controversial issue (which often separates analytical psychology and psychoanalysis) of whether expressive therapy should be used in analysis at all.

In the second half of the nineteenth century an awareness slowly developed that painting held within itself the power to tap into that part of the psyche where the passions lie. Music was the ideal example of this, for it had the power to do this without resorting to mimesis, narrative or language. The question was asked again and again by artists and critics whether paint and color could do the same, and with each successive query abstraction became progressively inevitable. Throughout the process music served as a model and a guide, and this, in all likelihood, would not have been the case without an easy access to music, and this was provided by the nineteenth century phenomenon of the piano.

The focus in hearing aids is generally on speech, but the ability to reproduce music is also important for listener satisfaction. This study uses a sound quality metric to predict judgments of music quality made by normal‐hearing and hearing‐impaired listeners. A simulated hearing aid was used to process music modified by (1) additive noise and nonlinear processing, (2) linear filtering, and (3) combinations of noise, nonlinear processing, and linear filtering. The music stimuli included jazz, classical, and vocalize selections. The quality metric incorporates a model of the auditory periphery that reproduces aspects of impaired hearing. The effects of noise and distortion on the signal are estimated by measuring the changes to the envelope time‐frequency modulation pattern, and the effects of linear filtering are estimated by measuring the changes to the signal long‐term internal spectral representation. The accuracy of the quality metric for music will be presented, and the performance of the metric for music will be compared to its accuracy in reproducing the quality ratings of speech stimuli processed under similar conditions.

This paper is a brief overview of the research and didactic activities of the Laboratorio di Informatica Musicale (L.I.M.) of the University of Milan. The main goals at L.I.M. are the definition of formal methods and the implementation of software and hardware tools to process music (both in real time and in interactive mode) at various abstraction levels.

To process music might appear easy, but to exchange musical information, in real time, between a computer and a device seems more difficult. Our paper presents a realization of a musical peripheral built with an electronic organ and that allows a computer to get the information that comes from the keyboard or play music on the organ.The system is not too complex because our first preocupation was to encode music under a digital form, and then to create automatically the encoding. We present algorithms, realizations and perspectives.

This article explores the way that the performance of temporal processes in recent contemporary music reveals something about the nature of musical time. Process music deals with time as a part of its material, offering the opportunity to experience time as time: the expression and experience of units of time that are defined by, and enclose, processes, in works whose forms are defined by their durations. This experience of musical time has been described by Kramer as 'vertical time' (1981/1988): the extended perception of a single moment. Such an experience can be identified in Gisby's Iterative Music (2012-) and Zaldua's Foreign Languages (2013-17). The moment-to-moment sonic details of the works are undefined and are discoverable only as they unfold, highlighting the unpredictability of sometimes highly prescriptive music. Bergson's (1889;1910) Time and Free Will outlines the distinction between time as units of duration and 'real duration', which is the experience of time passing in the present. In the latter case, "several conscious states are organized into a whole, permeate one another, gradually gain a richer content" (1910, 122). The duration of Spahlinger's Eigenzeit from Vorslage (1992-93) is determined by its processes, which are undetermined until they are enacted. Stone furthers this in As sure as time... (2016-) by imagining each performance as a unit of duration in a theoretical meta-performance. These pieces show how the performance of the temporal process makes concrete the quantitative nature of duration and shifts the focus of the listener to vertical time.