15 citations · 27 across the 4 of their papers we have counts for
7 papers · 1 filter
DeePAQ: A Perceptual Audio Quality Metric Based On Foundational Models and Weakly Supervised Learning
Guanxin Jiang, Andreas Brendel, Pablo M. Delgado +1
This paper presents the Deep learning-based Perceptual Audio Quality metric (DeePAQ) for evaluating general audio quality. Our approach leverages metric learning together with the…
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…
An Improved Metric of Informational Masking for Perceptual Audio Quality Measurement
Pablo M. Delgado, Jürgen Herre
Perceptual audio quality measurement systems algorithmically analyze the output of audio processing systems to estimate possible perceived quality degradation using perceptual mode…
A Data-driven Cognitive Salience Model for Objective Perceptual Audio Quality Assessment
Pablo M. Delgado, Jürgen Herre
Objective audio quality measurement systems often use perceptual models to predict the subjective quality scores of processed signals, as reported in listening tests. Most systems…
Can we still use PEAQ? A Performance Analysis of the ITU Standard for the Objective Assessment of Perceived Audio Quality
Pablo M. Delgado, Jürgen Herre
The Perceptual Evaluation of Audio Quality (PEAQ) method as described in the International Telecommunication Union (ITU) recommendation ITU-R BS.1387 has been widely used for compu…
Objective Assessment of Spatial Audio Quality using Directional Loudness Maps
Pablo M. Delgado, Jürgen Herre
This work introduces a feature extracted from stereophonic/binaural audio signals aiming to represent a measure of perceived quality degradation in processed spatial auditory scene…