Page 133 - Weiss, Jernej, ur./ed. 2025. Glasbena interpretacija: med umetniškim in znanstvenim┊Music Interpretation: Between the Artistic and the Scientific. Koper/Ljubljana: Založba Univerze na Primorskem in Festival Ljubljana. Studia musicologica Labacensia, 8
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Weiss, Jernej, ur. 2025. Glasbena interpretacija: med umetniškim in znanstvenim | Music Interpretation: Between the Artistic and the Scientific.
                         Koper/Ljubljana: Založba Univerze na Primorskem in Festival Ljubljana. https://doi.org/10.26493/978-961-293-425-5.133-146
                         © 2025 Wolfgang Marx











                 AI and Musical Interpretation

                 Wolfgang Marx
                 Univerzitetni kolidž v Dublinu
                 University College Dublin




                 Introduction
            It was only a question of time until generative artificial intelligence (AI)
            would move on from creating texts and pictures to the creation of music.
            While general AI content generators are expanding more and more into
            the music area, there are now also more and more music-specific generative
                                   1
                                             2
                                                                          3
            AI systems such as Udio,  Soundraw  and DeepAI Music Generator.  Many
            of them are accessible for free, although using the full range of capabilities
            usually requires signing up for a paid subscription. What is the potential
            impact of AI-generated music on questions of musical interpretation? My
            argument will be developed in three steps: firstly, a number of examples of
            AI-generated songs are presented in order to outline what AI can do at the
            moment. Secondly, the way in which large language models (LLMs) – the
            underlying systems of many AI generators – work is discussed, showing
            that LLMs have a tendency to standardise their results, while also remov-
            ing any quirk or idiosyncrasy that human creators would (unconsciously)
            include. AI outputs are “depersonalised”, as it were. Thirdly, the concept
            of “model collapse” is introduced. It leads to further homogenisation as AI
            systems will inevitably include more and more data in their processes that
            are already AI-created, setting in motion a spiral of self-referentiality that
            1    Udio Beta, https://www.udio.com/.
            2    Soundraw, https://soundraw.io/.
            3    Deep AI Music Generator, https://deepai.org/music.


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