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Jesús Monge-Álvarez

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • eess.AS2
  • cs.LG1
ORCID 0000-0002-5579-1394

identity via Semantic Scholar / OpenAlex

most citedA Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features

65 citations · 65 across the 3 of their papers we have counts for

collaborators

3 papers

eess.AS2025

Improving Resource-Efficient Speech Enhancement via Neural Differentiable DSP Vocoder Refinement

Heitor R. Guimarães, Ke Tan, Juan Azcarreta +4

Deploying speech enhancement (SE) systems in wearable devices, such as smart glasses, is challenging due to the limited computational resources on the device. Although deep learnin…

cs.LG2025

Efficient Neural and Numerical Methods for High-Quality Online Speech Spectrogram Inversion via Gradient Theorem

Andres Fernandez, Juan Azcarreta, Cagdas Bilen +1

Recent work in online speech spectrogram inversion effectively combines Deep Learning with the Gradient Theorem to predict phase derivatives directly from magnitudes. Then, phases…

eess.AS2024★ 65 cited

A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features

Jesús Monge-Alvarez, Carlos Hoyos-Barceló, Luis M. San-José-Revuelta +1

Cough is a protective reflex conveying information on the state of the respiratory system. Cough assessment has been limited so far to subjective measurement tools or uncomfortable…

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