On the Development and Practice of AI Technology for Contemporary Popular Music Production

Deruty, Emmanuel; Grachten, Maarten; Lattner, Stefan; Nistal, Javier; Aouameur, Cyran

doi:10.5334/tismir.100

Cited by 16 publications

(7 citation statements)

References 19 publications

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“…In Deruty et al (2022), music production of contemporary pop music is carried out using AI tools. Different musical instrument sound generation tools are utilized with automatic music labeling features in the form of symbolic representations and the coupling of composition with sound editing and mixing.…”

Section: Music Information Retrieval and Recent Techniquesmentioning

confidence: 99%

Resource building and classification of Mizo folk songs

Ramdinmawii,

Nath

2024

Nat. lang. processing

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Folk culture represents the social, ethnic, and traditional livelihood of people belonging to a certain tribe or community and is important in keeping their culture and tradition alive. The Mizo people are a Tibeto-Burmese ethnic group, native to the Indian state of Mizoram and neighboring regions of Northeast India. Mizo folk culture is an amalgamation of festivity, celebration, liveliness, kinship, brotherhood, and merriment, and above all, preserves the ethnicity of this tribal community that is fundamentally entrenched. Unfortunately, the Mizos are fast giving up their old customs and adopting the new mode of life that is greatly influenced by the western culture. This makes it all the more crucial to preserve the intangible cultural heritage of this ethnic tribe whose folk cultures are vanishing day by day. To the best of our knowledge, this work is the first attempt at preservation and classification of Mizo folk songs. The first part of this paper presents a literature survey on preservation, analysis, and classification of folk songs. The second part presents the methodology for preliminary classification of Mizo folk songs. Three categories of Mizo folk songs—Hunting chants (Hlado), Children’s songs (Pawnto hla), and Elderly songs (Pi pu zai)—are used in this study. A total of 29 acoustic features are used. A long short-term memory network using custom attention layer has been proposed for classification, whose results are compared with four supervised models (Support Vector Machines, K-Nearest Neighbor, Naive Baye’s, and Ensemble). Experimental results from the proposed model are promising, with an implication of scope for future research in acoustic analysis and classification of Mizo folk songs using recent unsupervised methods.

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Section: Music Information Retrieval and Recent Techniquesmentioning

confidence: 99%

Resource building and classification of Mizo folk songs

Ramdinmawii,

Nath

2024

Nat. lang. processing

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“…Audio sampling technology has evolved over several decades, not limited to modern music but also encompassing the collection of sounds from various sources, including ethnic music, world music, orchestral, jazz, and music from all corners of the globe. It has become a valuable tool for music creators and producers, especially those with budget constraints, as it offers cost-effective alternatives to folk music production (Nopparat & Narkkong, 2019;Wang & Yu, 2020;Rambarran, 2021;Shang & Wang, 2022;Deruty et al, 2022).…”

Section: Background and Rationalementioning

confidence: 99%

A Study of Isan Folk Music Creation Using a Sampler for Music Education

Khuntajan

2024

JEL

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This research represents a creative exploration in the field of music (Practice as Research: PaR) with the objectives of 1) studying the use of a sampler from Isan instruments and instruments from various cultures to create musical compositions using music software, and 2) examining the appropriate contexts for using a sampler in creative musical works. The research findings reveal that 1) Isan folk music possesses unique characteristics in terms of sound quality and performance techniques, while other musical elements can be combined with it in a technologically driven creative process. This involves connecting the concepts and methods of both traditional and diverse cultural music to create unified compositions using technology, such as recording musical notes in standard notation, exporting them as MIDI files, and then importing them into audio recording software to refine the sounds for complete songs. 2) Regarding the appropriate contexts for using a sampler in creative music, three main contexts were identified: an Isan folk music composition context, a music education context, and a commercial or music business context. In summary, the process of using a sampler for creative music works can bridge the concepts of various cultural music and integrate them with technology. Furthermore, this process can be extended to enhance interdisciplinary learning and teaching methods, making it applicable in diverse contexts.

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“…The literature has captured the advantages of AI-facilitated music creation, including breaking conventional musical structures, enabling listeners to tailor music, and adapting lyrics and vocal styles to suit various cultural contexts ( Civit et al, 2022 ; Deruty et al, 2022 ). As a result, non-professional non-professional content creators can modify lyrics and infuse local elements to create personalized songs in response to special events (e.g., birthdays, celebrations, and social incidents).…”

Section: Introductionmentioning

confidence: 99%

Enhancing social media engagement using AI-modified background music: examining the roles of event relevance, lyric resonance, AI-singer origins, audience interpretation, emotional resonance, and social media engagement

2024

Front. Psychol.

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IntroductionDrawing on the S-O-R model, this study aims to investigate the influence of three stimuli from AI-modified music (i.e., event relevance, lyric resonance, and AI-singer origins), two responses from social media content consumers (i.e., audience interpretation and emotional resonance) on the social media engagement of personalized background music modified by artificial intelligence (AI).MethodsThe structural equation modeling analyses of 467 social media content consumers’ responses confirmed the role of those three stimuli and the mediating effect of audience interpretation and emotional resonance in shaping social media engagement.ResultsThe findings shed light on the underlying mechanisms that drive social media engagement in the context of AI-modified background music created for non-professional content creators.DiscussionThe theoretical and practical implications of this study advance our understanding of social media engagement with AI-singer-originated background music and provide a basis for future investigations into this rapidly evolving phenomenon in the gig economy.

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On the Development and Practice of AI Technology for Contemporary Popular Music Production

Cited by 16 publications

References 19 publications

Resource building and classification of Mizo folk songs

Resource building and classification of Mizo folk songs

A Study of Isan Folk Music Creation Using a Sampler for Music Education

Enhancing social media engagement using AI-modified background music: examining the roles of event relevance, lyric resonance, AI-singer origins, audience interpretation, emotional resonance, and social media engagement

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