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Search and discover 100M+ tracks with AI audio embeddings and language models
- anonauthority 3y agoHi! 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/ https://speakmusic.sonophase.com/ Our friends and colleagues have been encouraging us to release it publicly, so here it is! We recently presented it at Sonar+D in Barcelona. We’ve trained an AI model to understand the correspondence between music and language. We combine a machine listening system for audio signal processing with transformers for text embeddings. Once trained, we index a huge catalogue of unseen audio, ensuring that the search system can efficiently scale to millions of tracks. At the moment, our model is optimised for our preferred music; electronic and 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!