6 citations · 8 across the 2 of their papers we have counts for
2 papers
eess.AS2024★ 2 cited
FlowMAC: Conditional Flow Matching for Audio Coding at Low Bit Rates
Nicola Pia, Martin Strauss, Markus Multrus +1
This paper introduces FlowMAC, a novel neural audio codec for high-quality general audio compression at low bit rates based on conditional flow matching (CFM). FlowMAC jointly lear…
eess.AS2023★ 6 cited
SEFGAN: Harvesting the Power of Normalizing Flows and GANs for Efficient High-Quality Speech Enhancement
Martin Strauss, Nicola Pia, Nagashree K. S. Rao +1
This paper proposes SEFGAN, a Deep Neural Network (DNN) combining maximum likelihood training and Generative Adversarial Networks (GANs) for efficient speech enhancement (SE). For…