output
20162026
most citedMulti-Speaker DOA Estimation Using Deep Convolutional Networks Trained with Noise Signals

328 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing 2024Show all

3 papers · 1 filter

eess.AS2024★ 4 cited

Towards Improved Objective Perceptual Audio Quality Assessment -- Part 1: A Novel Data-Driven Cognitive Model

Pablo M. Delgado, Jürgen Herre

Efficient audio quality assessment is vital for streamlining audio codec development. Objective assessment tools have been developed over time to algorithmically predict quality ra…

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.SP2024

Model-Based Deep Learning for Music Information Research

Gael Richard, Vincent Lostanlen, Yi-Hsuan Yang +1

In this article, we investigate the notion of model-based deep learning in the realm of music information research (MIR). Loosely speaking, we refer to the term model-based deep le…