Musicians' Attitudes to Musical Influence

Collins, Nick

doi:10.18061/1811/51204

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…8 Corpus-based composition systems have an advantage in that they make absolutely explicit what influences they require. However, study of musicians' attitudes to influence has shown that humans are not overly anxious about influence (Collins, 2011). A richly creative AI may need to forget the circumstances of its learning about a particular training example, so as not to be overly burdened by the weight of history.…”

Section: Listening To Everythingmentioning

confidence: 99%

“… there is no reason why it should ever stop”: Large-scale algorithmic composition

Collins

2018

Journal of Creative Music Systems

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This article surveys some new directions in algorithmic composition, with a special focus on the mass scale of content generation now within reach. Interest in algorithmic composition has recently flourished, including a fashion for deep learning, and commercial offshoots in apps and browser software. Whilst there is much to be excited about in recent developments, we critically survey some current directions, and likely future initiatives, of the field. In particular, the influence of and potential within music information retrieval research is highlighted, corresponding to attempts to bridge between audio machine listening and large corpus training for algorithmic composition. The scenario of mass generation is further considered, including a practical experiment in creating a billion melody data set with accompanying source code.

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Section: Listening To Everythingmentioning

confidence: 99%

“… there is no reason why it should ever stop”: Large-scale algorithmic composition

Collins

2018

Journal of Creative Music Systems

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“…When machines are involved in making musical judgments, the volume of reference can potentially scale up to even more depressing or exciting a degree, depending on a creator's perspective. In the main, positive benefits of historical awareness and the potential for new "database music" may be hoped to dominate: A recent online study of musicians' attitudes to influence found no strong evidence for any 'anxiety of influence' and most musicians in the survey welcomed a sense of musical history and culture [Collins 2011].…”

Section: Algorithmic Critic Technologymentioning

confidence: 99%

Towards Machine Musicians Who Have Listened to More Music Than Us

Collins

2016

Comput. Entertain.

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Databases of audio can form the basis for new algorithmic critic systems, applying techniques from the growing field of music information retrieval to meta-creation in algorithmic composition and interactive music systems. In this article, case studies are described where critics are derived from larger audio corpora. In the first scenario, the target music is electronic art music, and two corpuses are used to train model parameters and then compared with each other and against further controls in assessing novel electronic music composed by a separate program. In the second scenario, a “real-world” application is described, where a “jury” of three deliberately and individually biased algorithmic music critics judged the winner of a dubstep remix competition. The third scenario is a live tool for automated in-concert criticism, based on the limited situation of comparing an improvising pianists' playing to that of Keith Jarrett; the technology overlaps that described in the other systems, though now deployed in real time. Alongside description and analysis of these systems, the wider possibilities and implications are discussed.

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“…For example, in a large survey of 244 respondents, Creech et al (2008) corroborated that important factors of influence for classical musicians included teachers, parents, peers and specific musical events, and for non-classical musicians factors also included the influence of well-known performers (p. 226). In another large study of 119 respondents, Collins (2011) examined issues of musical influence and reported that, although advanced musicians nurture, on the whole, a positive attitude towards influence (pp. 103, 118), the sources of influence can change over time (p. 113).…”

Section: Introductionmentioning

confidence: 99%

Performers’ discourses on listening to recordings

Volioti

Williamon

2020

Research Studies in Music Education

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How we listen to music and respond to its media and contexts has changed significantly since the invention of sound recording. Today’s musicians have countless opportunities to listen to others’ interpretations given the vast availability of past and contemporary repertories through the global reach of recordings. This study investigated the extent to which the growing archive of recordings provides a valuable resource for performers’ creativity. Although musical performance is a particularly porous domain for influence through either deliberate or spontaneous assimilation of expressive variation from other aural sources, little empirical research exists on influence in performance and specifically on the influence of recordings. Qualitative data were obtained via an online questionnaire to identify how and in what ways the use and influence of recordings have changed over the course of classical performers’ training or professional careers. Respondents’ ( N = 130) comments were analysed using a thematic inductive approach. The emerging themes reveal an overall increased level of use of recordings now relative to the past, a largely positive contribution of recordings in shaping musical development, including the role of recordings in self-regulated learning, a largely positive attitude to the influence of others’ interpretations, a means of developing expressions of self-identity in relation to others and a route to acquiring a more critical and discerning mode of listening to recordings. Implications for music education are discussed in terms of how listening to recordings, in both formal and informal learning contexts, could support advanced musicians’ learning through trial and error, enhance creative insight, strengthen self-efficacy, foster metacognitive skills and nurture individuality.

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Musicians' Attitudes to Musical Influence

Cited by 4 publications

References 20 publications

“… there is no reason why it should ever stop”: Large-scale algorithmic composition

“… there is no reason why it should ever stop”: Large-scale algorithmic composition

Towards Machine Musicians Who Have Listened to More Music Than Us

Performers’ discourses on listening to recordings

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