Title: In 2020, Magenta released DDSP [1], a machine learning algorithm &#x2F; 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.<p>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 fine-tuning parts of the model to the new recording. This allows us to produce decent sounding instrument synthesisers from as little as 16 seconds of target audio instead of 6-10 minutes.<p>[1] <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2001.04643" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2001.04643</a><p>[2] <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;1802.06006" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;1802.06006</a><p>[3] <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2006.07931" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2006.07931</a><p>We hope to publish a paper on the topic soon.
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