Designing Computationally Creative Musical Performance Systems

Goddard, Callum; Barthet, Mathieu; Wiggins, Geraínt A.

doi:10.1145/3123514.3123541

Cited by 2 publications

(7 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Please refer to Goddard et al [4] for further explanation of the CSF symbols and the components they refer to.…”

Section: Per F Ormancementioning

confidence: 99%

“…We take value to be "a relation between an artifact, its creator and its observers and the context in which creation and observation takes place" [22, p.2]. For further explanation of the CSF and its components, please see [4].…”

Section: The Creative Systems Frameworkmentioning

confidence: 99%

“…Previously in [4] we produced a formalized system design in terms of the CSF for a performance system that uses case-based reasoning to produce virtuosic interpretations of a piece of music. We also briefly discussed one potential implementation.…”

Section: The Systemmentioning

confidence: 99%

“…This capability to reflect is crucial to creative systems [2,3] and semantic information can be used to aid in the evaluation and reasoning that guides the system's reflection process. However, because it is more common for previous work developing musical performance systems, such as Computer Systems for Expressive Musical Performance (CSEMP) to not employ a full reflection loop or self-reasoning, we proposed in [4] to use the Creative Systems Framework (CSF) by Wiggins [5,6] as a design tool to frame and describe both new or even existing CSEMPs as creative systems (should their authors wish to turn them into creative systems).…”

Section: Introductionmentioning

confidence: 99%

“…We relied on the CSF to design a new computationally creative music performance system that uses case-based reasoning to produce virtuosic musical performances with a physical model of a bass guitar (selected due to author expertise and experience with the instrument, and to allow for nuanced control of the performance rendering) [4]. Here, we refine the system implementation and focus on the measure of musical similarity used within our casebased reasoning system.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Assessing Musical Similarity for Computational Music Creativity

Goddard¹,

Barthet²,

Wiggins³

2018

J. Audio Eng. Soc.

Self Cite

View full text Add to dashboard Cite

Computationally creative systems require semantic information when reflecting or self reasoning on their output. In this paper we outline the design of a computationally creative musical performance system aimed at producing virtuosic interpretations of musical pieces and provide an overview of its implementation. The case-based reasoning part of the system relies on a measure of musical similarity based on the FANTASTIC and SynPy toolkits that provide melodic and syncopated rhythmic features, respectively. We conducted a listening test based on pair-wise comparison to assess to what extent the machine-based similarity models match human perception. We found the machine-based models to differ significantly to human responses due to differences in participants' responses. The best performing model relied on features from the FANTASTIC toolkit obtaining a rank match rate with human response of 63%, while features from the SynPy toolkit only obtained a ranking match rate of 46%. While more work is needed on a stronger model of similarity, we do not believe these results prevent FANTASTIC features being used as a measure of similarity within creative systems.

show abstract

“…Please refer to Goddard et al [4] for further explanation of the CSF symbols and the components they refer to.…”

Section: Per F Ormancementioning

confidence: 99%

Section: The Creative Systems Frameworkmentioning

confidence: 99%

Section: The Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Assessing Musical Similarity for Computational Music Creativity

Goddard¹,

Barthet²,

Wiggins³

2018

J. Audio Eng. Soc.

Self Cite

View full text Add to dashboard Cite

show abstract

Neural electric bass guitar synthesis framework enabling attack-sustain-representation-based technique control

Koguchi,

Morise

2024

J AUDIO SPEECH MUSIC PROC.

View full text Add to dashboard Cite

Musical instrument sound synthesis (MISS) often utilizes a text-to-speech framework because of its similarity to speech in terms of generating sounds from symbols. Moreover, a plucked string instrument, such as electric bass guitar (EBG), shares acoustical similarities with speech. We propose an attack-sustain (AS) representation of the playing technique to take advantage of this similarity. The AS representation treats the attack segment as an unvoiced consonant and the sustain segment as a voiced vowel. In addition, we propose a MISS framework for an EBG that can control its playing techniques: (1) we constructed a EBG sound database containing a rich set of playing techniques, (2) we developed a dynamic time warping and timbre conversion to align the sounds and AS labels, (3) we extend an existing MISS framework to control playing techniques using AS representation as control symbols. The experimental evaluation suggests that our AS representation effectively controls the playing techniques and improves the naturalness of the synthetic sound.

show abstract

Designing Computationally Creative Musical Performance Systems

Cited by 2 publications

References 25 publications

Assessing Musical Similarity for Computational Music Creativity

Assessing Musical Similarity for Computational Music Creativity

Neural electric bass guitar synthesis framework enabling attack-sustain-representation-based technique control

Contact Info

Product

Resources

About