Stable Audio 2.0
One shot sample generation for the SignalsAndSorcery.com platform - shiehn/sas-sample-generator
Stable Audio 2.0 launched on April 4, 2024 with 156 votes, #317 of 4,347 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 2 years on.
What it does
Our new model takes AI music generation to the next level by letting you generate high-quality audio up to 3 minutes. Everyone can generate audio up to 3 minutes in length, including our free plan users!
Today, we are pleased to introduce Stable Audio 2.0. This model enables high-quality, full tracks with coherent musical structure up to three minutes long at 44.1 kHz stereo from a single natural language prompt.
Stable Audio 2.0 sets a new standard in AI-generated audio, producing high-quality, full tracks with coherent musical structure up to three minutes in length at 44.1kHz stereo. The new model introduces audio-to-audio generation by allowing users to upload and transform samples using natural language prompts. Stable Audio 2.0 was exclusively trained on a licensed dataset from the AudioSparx music library, honoring opt-out requests and ensuring fair compensation for creators. Explore the model and start creating for free on the Stable Audio website now. Today, we are pleased to introduce Stable Audio 2.0 . This model enables high-quality, full tracks with coherent musical structure up to…from stability.ai
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Cloning a musical instrument from 16 seconds of audio2022 · erlj.notion.site · ▲185In 2020, Magenta released DDSP [1], a machine learning algorithm / python library which made it possible to generate good sounding instrument synthesizers from about 6-10 minutes of data. While working with DDSP for a project, we realised how it was actually quite hard to find 6-10 minute of clean recordings of monophonic instruments. In this project, we have combined the DDSP architecture with a domain adaptation technique from speech synthesis [2]. This domain adaptation technique works by pre-training our model on many different recordings from the Solos dataset [3] first and then…



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