Kinyugo Maina

ML Engineer & Researcher

Biography

Hello, I’m Kinyugo Maina, a Machine Learning Engineer and Researcher specializing in Generative AI. With a background in Computer Science, I create AI-driven solutions across virtual try-on, music synthesis, and virtual product photography, leveraging deep learning to tackle real-world challenges. I'm passionate about advancing Generative AI and contributing to this growing field.

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Featured Publications

arXiv January 16th, 2023
Msanii: High Fidelity Music Synthesis on a Shoestring Budget

Kinyugo Maina - Independent Researcher

kinyugomaina@gmail.com

In this paper, we present Msanii, a novel diffusion-based model for synthesizing long-context, high-fidelity music efficiently. Our model combines the expressiveness of mel spectrograms, the generative capabilities of diffusion models, and the vocoding capabilities of neural vocoders. We demonstrate the effectiveness of Msanii by synthesizing tens of seconds (190 seconds)...

Sound Machine Learning Audio and Speech Processing

Featured Projects

Msanii

Official implementation of the Msanii paper. The paper introduces a novel diffusion based model for audio synthesis. It outperforms existing diffusion models in terms of fidelity, long-term coherence and efficiency.

Music Synthesis Paper PyTorch WiP
odewel

odewel (/əʊdwel/) is a library that can optimize machine learning models for better efficiency by loading weights only when needed for computation. This makes the models leaner and more nimble, and allows them to run on any hardware, regardless of its size or the hardware capabilities.

Model Inference PyTorch WiP