{
  "id": 4025237,
  "title": "A behaviourally normed database of 1,377 natural sounds for auditory cognition and neuroscience",
  "url": "https://urgent.news/2026/08/28/a-behaviourally-normed-database-of-1-377-natural-sounds-for-auditory",
  "topic": "science",
  "section": "Science",
  "published": "2026-08-28T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.08.25.746933v1?rss=1"
  },
  "original_language": "en",
  "account": "The MaMa Sounds database, a compilation of 1,377 natural sounds, has been developed to facilitate auditory cognition and neuroscience research. This extensive collection, comprising two-second sounds representing 240 distinct source-action classes, marks a collaborative effort between academic teams in Maastricht and Marseille.\n\nEach sound in the database has been meticulously curated and segmented, sampled at a rate of 16 kHz, and accurately labeled with a noun identifying the sound source and a verb describing the action. The dataset is enriched with comprehensive deidentified trial-level data, including identification accuracy, confidence, agreement, and familiarity metrics. Furthermore, the database incorporates multiple per-sound norms, derived through principal component analysis, to offer valuable insights into sound identification and familiarity.\n\nThe database provides a rich set of norms, including noun, verb, and joint noun-verb norms, presented as direct means and medians along with the number of contributing observations. These norms preserve process-specific information, while two principal-component scores offer compact overall behavioral-identifiability measures. These measures are derived from response ease, semantic correspondence, agreement, and familiarity, providing a concise summary of the data.\n\nIn addition to the sound data and norms, the MaMa Sounds repository also includes deterministic response-cleaning code, participant and reference Word2Vec representations, and code to reproduce public sound-level tables. This comprehensive resource is designed to support various applications in auditory cognition and neuroscience, such as stimulus selection, matching, and continuous modeling.",
  "summary": "Natural-sound research requires stimulus sets that combine acoustic standardization with detailed behavioural characterization. We present 1,377 two-second sounds representing 240 expert-defined source--action classes. We call this database \"MaMa Sounds\", as it resulted from the collaborative effort of two academic teams in Maastricht and Marseille. The sounds were manually curated, segmented,…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}