<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/5a4f0bffb32d4d9b874194d81310b21c&quot; frameborder=&quot;0&quot; width=&quot;1664&quot; height=&quot;1248&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1248</height><width>1664</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1248</thumbnail_height><thumbnail_width>1664</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/5a4f0bffb32d4d9b874194d81310b21c-00001.gif</thumbnail_url><duration>561.7456120030001</duration><title>Creating a Lo-Fi Bollywood Sample with AI</title><description>In this video, I demonstrate how I used AI to generate a lo-fi Bollywood sample. I explore different music generation techniques using audio clips and text. I start with a recent paper called MusicGen by Facebook, which generates waveforms and allows conditioning on both text and melody. However, the initial model didn&apos;t capture the lo-fi element I was looking for, so I fine-tuned it using a dataset of 150 songs with lo-fi characteristics. I then add human intervention by editing the clip, adding reverb, slowing it down, and incorporating Eastern instrumentals. Finally, I experiment with extending the AI-generated track using text prompts. Although there are limitations, this approach shows promise for longer track generation and transitioning between themes. Code and notebook to follow.</description></oembed>