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{
    "pk": 24616,
    "title": "Inferring Musical Structure - A Hybrid Approach Combining Probabilistic Models and Reinforcement Learning",
    "subtitle": null,
    "abstract": "How do humans infer the structural interpretations of a piece of music from its basic elements? Since recursive elaboration is an important structural principle in several musical traditions, generative probabilistic models are a useful tool for characterizing musical interpretation as a probabilistic inference problem. However, due to the high degree of ambiguity and combinatorial complexity of even short excerpts of music, exact inference (e.g. finding the \"best\" structural interpretation of a piece) is usually not feasible. The present work proposes a hybrid approach to this problem. An explicit and interpretable probabilistic top-down model is complemented with a heuristic parser that reverses the generative process in a greedy fashion and adapts to feedback from the top-down model via deep reinforcement learning. The combination of these two models bridges the gap between explicit but slow top-down knowledge and immediate musical intuitions on various levels of musicianship.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Machine learning; Music; Perception; Bayesian modeling; Computational Modeling"
        }
    ],
    "section": "Abstracts",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/5g10x1pv",
    "frozenauthors": [
        {
            "first_name": "Christoph",
            "middle_name": "",
            "last_name": "Finkensiep",
            "name_suffix": "",
            "institution": "University of Amsterdam",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2024-01-01T11:00:00-07:00",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24616/galley/17976/download/"
        },
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24616/galley/21279/download/"
        }
    ]
}