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Musical Events Scatterplot

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Musical Events Scatterplot

In the process of working on models that decompose audio into sparse representations, I've found that it can be fun to explore the space of possible musical events that the learned decoders can produce. Most modern "neural" codecs encode fixed-size "frames" of audio. This work models sound as a sparse set of events and physical resonances, which could yield benefits for compression, intrepetability, classification, and beyond. Here, I map 32-dimensional event vectors onto a 2D plane via t-SNE. Each event can be played by clicking or tapping.

Visit productView on Hacker NewsDec 12, 2024
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, presentations · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

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