Emilia Parada-Cabaleiro

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Junior Professor

Hochschule für Musik Karlsruhe

Germany

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About

Emilia Parada-Cabaleiro is a Junior Professor at Nuremberg University of Music in Germany. Her research focuses on speech emotion recognition, multi-modal perception of music, and the psychological implications of music on anxiety. She has published various articles exploring the intersection of technology and music, including advancements in machine learning applications for emotion recognition and recommendations in the music domain.

Recent Grants

Grant: Close

Melody of Crisis/Joy

Open Date: 2022-03-01

Close Date: 2022-09-01

Grant: Close

EmoMTB (Emotion-aware music tower blocks)

Open Date: 2021-02-01

Close Date: 2021-09-01

Articles (10)

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2025

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2021

Year:

2020

Collaborators (3)

Markus Schedl

Full Professor

Johannes Kepler University Linz

AUSTRIA

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Valerio Cesarini

University of Rome Tor Vergata

ITALY

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Giovanni Costantini

University of Rome Tor Vergata

ITALY

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Emilia Parada-Cabaleiro

Research Interests

Explore related searches

Contact this professor

About

Recent Grants

Articles (10)

A Residual Multi-Scale Convolutional Neural Network With Transformers for Speech Emotion Recognition

Exploring emotions in Bach chorales: a multi-modal perceptual and data-driven study

Emotion-aware music tower blocks (EmoMTB ): an intelligent audiovisual interface for music discovery and recommendation

Perception and classification of emotions in nonsense speech: Humans versus machines

An Exploratory Study on the Acoustic Musical Properties to Decrease Self-Perceived Anxiety

The Emotion Probe: On the Universality of Cross-Linguistic and Cross-Gender Speech Emotion Recognition via Machine Learning

Correction to: The perception of emotional cues by children in artificial background noise

The effect of music in anxiety reduction: A psychological and physiological assessment

Investigating gender fairness of recommendation algorithms in the music domain

DEMoS: an Italian emotional speech corpus: Elicitation methods, machine learning, and perception

Collaborators (3)

Markus Schedl

Valerio Cesarini

Giovanni Costantini

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