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    "story_id": "mp-2026-09-12-009",
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    "section": "robotics",
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    "headline": "Nonprofessionals Could Not Tell the Robot Pianist From a Human",
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    "dek": "Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.",
    "summary": "Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.",
    "body_text": "The robotic pianist uses graph optimization to choose natural pre-press and key-press finger transitions, then a physics-inspired acoustic model varies key velocity with the musical score. The authors report gains over baselines in motion similarity and dynamic accuracy across multiple styles. In listening tests, participants preferred the expressive system to baseline robot performances; nonprofessional listeners rated it indistinguishably from human performances. That perceptual result is limited to the reported audience and repertoire, not a general claim of human-level musicianship.",
    "why_it_matters": "Graph-guided fingering and a physics-inspired acoustic model paired mechanical accuracy with score-level dynamics.",
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      "That perceptual result is limited to the reported audience and repertoire, not a general claim of human-level musicianship."
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    "tags": [
      "robotics",
      "music",
      "dexterous manipulation"
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    "image_url": null,
    "corrections": []
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  "sources": [
    {
      "source_id": "source-2026-09-12-009",
      "title": "arXiv preprint 2609.10844",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2609.10844",
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    "name": "The Machine Press",
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    "description": "A daily newspaper for the age of artificial intelligence."
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    "title": "Nonprofessionals Could Not Tell the Robot Pianist From a Human",
    "publisher": "The Machine Press",
    "published_at": "2026-09-12T09:00:00.000-04:00",
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