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Project Qualia uncovers experiential music structure from listening data

By PulseAugur Editorial · [2 sources] ·

Researchers have developed Project Qualia, a method to uncover experiential similarities between songs using listening behavior data. By training a Word2Vec model on 531.6 million scrobbles from 9,396 users, they created a "Song2Vec" embedding space. After removing artist-specific data, the model identified 4,577 track pairs with high similarity, revealing genre- and era-based clusters independent of artist identity. AI

IMPACT This research demonstrates a novel application of NLP techniques to uncover subtle patterns in user-generated data, potentially influencing recommender systems.

RANK_REASON The cluster contains an academic paper detailing a new methodology for analyzing music structure.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Project Qualia uncovers experiential music structure from listening data

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The cluster contains an academic paper detailing a new methodology for analyzing music structure.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Nizam Mohammed, Abu B. S. Rahman, Dimuthu D. K. Arachchige ·

    Project Qualia: Recovering Experiential Music Structure from Session Co-occurrence Data

    arXiv:2609.10862v1 Announce Type: cross Abstract: This report presents results from Project Qualia, an ongoing effort to determine whether experiential similarity between songs, a structure not captured by genre or metadata taxonomies, can be recovered from real listening behavio…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Dimuthu D. K. Arachchige ·

    Project Qualia: Recovering Experiential Music Structure from Session Co-occurrence Data

    This report presents results from Project Qualia, an ongoing effort to determine whether experiential similarity between songs, a structure not captured by genre or metadata taxonomies, can be recovered from real listening behavior. We constructed a large-scale dataset of listeni…

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