AI + Apple Music, search 100M+ tracks with natural language prompts

Hacker News

Hi HN! We’re a group of electronic music artists and PhD researchers working in AI music. We've been working on a project to help us discover new music in a more musically objective way, called Speak Music: https://speakmusic.sonophase.com/ We recently presented at Sonar+D in Barcelona. We’ve trained an AI model to understand the correspondence between music and language, combining a machine listening system for audio signal processing with transformers for text embeddings. Once trained, we index a huge catalogue of unseen audio, so that the search system can efficiently scale to millions of tracks. At the moment, our model is optimised for our preferred music; electronic, techno, ambient and relaxing music. We’re currently fine-tuning to handle all kinds of genres and moods. Our model handles two types of discovery: (a) natural language search and (b) similarity search. (a) Speak: search for music using freeform natural language prompts, describing the mood, aesthetic, texture, setting and context of a track. (b) Music: discover tracks that are acoustically similar to ANY reference track from Apple Music. We hope you like it. Let us know what you think!

Visit product View on Hacker NewsJun 28, 2023

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Indie HackersFits the IH revenue-focused audience · Strong signals: efficiently · Missing: supports, reddit linkedin, podcasting

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TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

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AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive

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Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% 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

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