Generated Therapeutic Music Based on the ISO Principle

Zipeng Qiu; Ruibin Yuan; Wei Xue; Yucheng Jin

doi:10.1007/978-981-97-0576-4_3

Generated Therapeutic Music Based on the ISO Principle

Zipeng Qiu, Ruibin Yuan, Wei Xue, Yucheng Jin^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

2 Citations (Scopus)

Abstract

This paper presents an emotion-driven music generation model designed to support the development of an intelligent system to support music therapy informed by the ISO principle [1]. Following the ISO principle, the system’s primary objective is to generate music that aligns with patients’ emotions swiftly. To achieve this, we leverage a dataset for emotion recognition to fine-tune a pre-trained audio model, aiding in the annotation of a vast ABC notation dataset. Utilizing these annotated ABC notations, we employ a sequence generation model to build a system that could generate music according to the recognized emotions on the fly, thereby efficiently tailoring musical compositions to the emotional needs of patients in a therapeutic context.

Original language	English
Title of host publication	Music Intelligence
Subtitle of host publication	Second Summit, SOMI 2023, Beijing, China, October 28–30, 2023, Revised Selected Papers
Editors	Xiaobing Li, Xiaohong Guan, Yun Tie, Xinran Zhang, Qingwen Zhou
Place of Publication	Singapore
Publisher	Springer
Pages	32-45
Number of pages	14
Edition	1st
ISBN (Electronic)	9789819705764
ISBN (Print)	9789819705757
DOIs	https://doi.org/10.1007/978-981-97-0576-4_3
Publication status	Published - 3 Feb 2024
Event	2nd Summit on Music Intelligence, SOMI 2023 - Beijing, China Duration: 28 Oct 2023 → 30 Oct 2023 https://link.springer.com/book/10.1007/978-981-97-0576-4

Publication series

Name	Communications in Computer and Information Science
Volume	2007
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Name	SOMI: Summit on Music Intelligence

Conference

Conference	2nd Summit on Music Intelligence, SOMI 2023
Country/Territory	China
City	Beijing
Period	28/10/23 → 30/10/23
Internet address	https://link.springer.com/book/10.1007/978-981-97-0576-4

Scopus Subject Areas

Computer Science(all)
Mathematics(all)

User-Defined Keywords

Autoregressive
Emotion Recognition
Generative Models
Generative Music
Music Therapy
Sequence Generation
Transformer

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-981-97-0576-4_3

Cite this

Qiu, Z., Yuan, R., Xue, W., & Jin, Y. (2024). Generated Therapeutic Music Based on the ISO Principle. In X. Li, X. Guan, Y. Tie, X. Zhang, & Q. Zhou (Eds.), Music Intelligence: Second Summit, SOMI 2023, Beijing, China, October 28–30, 2023, Revised Selected Papers (1st ed., pp. 32-45). (Communications in Computer and Information Science; Vol. 2007), (SOMI: Summit on Music Intelligence). Springer. https://doi.org/10.1007/978-981-97-0576-4_3

Qiu, Zipeng ; Yuan, Ruibin ; Xue, Wei et al. / Generated Therapeutic Music Based on the ISO Principle. Music Intelligence: Second Summit, SOMI 2023, Beijing, China, October 28–30, 2023, Revised Selected Papers. editor / Xiaobing Li ; Xiaohong Guan ; Yun Tie ; Xinran Zhang ; Qingwen Zhou. 1st. ed. Singapore : Springer, 2024. pp. 32-45 (Communications in Computer and Information Science). (SOMI: Summit on Music Intelligence).

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title = "Generated Therapeutic Music Based on the ISO Principle",

abstract = "This paper presents an emotion-driven music generation model designed to support the development of an intelligent system to support music therapy informed by the ISO principle [1]. Following the ISO principle, the system{\textquoteright}s primary objective is to generate music that aligns with patients{\textquoteright} emotions swiftly. To achieve this, we leverage a dataset for emotion recognition to fine-tune a pre-trained audio model, aiding in the annotation of a vast ABC notation dataset. Utilizing these annotated ABC notations, we employ a sequence generation model to build a system that could generate music according to the recognized emotions on the fly, thereby efficiently tailoring musical compositions to the emotional needs of patients in a therapeutic context.",

keywords = "Autoregressive, Emotion Recognition, Generative Models, Generative Music, Music Therapy, Sequence Generation, Transformer",

author = "Zipeng Qiu and Ruibin Yuan and Wei Xue and Yucheng Jin",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 2nd Summit on Music Intelligence, SOMI 2023 ; Conference date: 28-10-2023 Through 30-10-2023",

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Qiu, Z, Yuan, R, Xue, W & Jin, Y 2024, Generated Therapeutic Music Based on the ISO Principle. in X Li, X Guan, Y Tie, X Zhang & Q Zhou (eds), Music Intelligence: Second Summit, SOMI 2023, Beijing, China, October 28–30, 2023, Revised Selected Papers. 1st edn, Communications in Computer and Information Science, vol. 2007, SOMI: Summit on Music Intelligence, Springer, Singapore, pp. 32-45, 2nd Summit on Music Intelligence, SOMI 2023, Beijing, China, 28/10/23. https://doi.org/10.1007/978-981-97-0576-4_3

Generated Therapeutic Music Based on the ISO Principle. / Qiu, Zipeng; Yuan, Ruibin; Xue, Wei et al.
Music Intelligence: Second Summit, SOMI 2023, Beijing, China, October 28–30, 2023, Revised Selected Papers. ed. / Xiaobing Li; Xiaohong Guan; Yun Tie; Xinran Zhang; Qingwen Zhou. 1st. ed. Singapore: Springer, 2024. p. 32-45 (Communications in Computer and Information Science; Vol. 2007), (SOMI: Summit on Music Intelligence).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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AU - Qiu, Zipeng

AU - Yuan, Ruibin

AU - Xue, Wei

AU - Jin, Yucheng

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

PY - 2024/2/3

Y1 - 2024/2/3

N2 - This paper presents an emotion-driven music generation model designed to support the development of an intelligent system to support music therapy informed by the ISO principle [1]. Following the ISO principle, the system’s primary objective is to generate music that aligns with patients’ emotions swiftly. To achieve this, we leverage a dataset for emotion recognition to fine-tune a pre-trained audio model, aiding in the annotation of a vast ABC notation dataset. Utilizing these annotated ABC notations, we employ a sequence generation model to build a system that could generate music according to the recognized emotions on the fly, thereby efficiently tailoring musical compositions to the emotional needs of patients in a therapeutic context.

AB - This paper presents an emotion-driven music generation model designed to support the development of an intelligent system to support music therapy informed by the ISO principle [1]. Following the ISO principle, the system’s primary objective is to generate music that aligns with patients’ emotions swiftly. To achieve this, we leverage a dataset for emotion recognition to fine-tune a pre-trained audio model, aiding in the annotation of a vast ABC notation dataset. Utilizing these annotated ABC notations, we employ a sequence generation model to build a system that could generate music according to the recognized emotions on the fly, thereby efficiently tailoring musical compositions to the emotional needs of patients in a therapeutic context.

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BT - Music Intelligence

A2 - Li, Xiaobing

A2 - Guan, Xiaohong

A2 - Tie, Yun

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PB - Springer

CY - Singapore

T2 - 2nd Summit on Music Intelligence, SOMI 2023

Y2 - 28 October 2023 through 30 October 2023

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Qiu Z, Yuan R, Xue W, Jin Y. Generated Therapeutic Music Based on the ISO Principle. In Li X, Guan X, Tie Y, Zhang X, Zhou Q, editors, Music Intelligence: Second Summit, SOMI 2023, Beijing, China, October 28–30, 2023, Revised Selected Papers. 1st ed. Singapore: Springer. 2024. p. 32-45. (Communications in Computer and Information Science). (SOMI: Summit on Music Intelligence). doi: 10.1007/978-981-97-0576-4_3