Search Results for author: Eric Guizzo

Found 5 papers, 5 papers with code

Learning Speech Emotion Representations in the Quaternion Domain

1 code implementation5 Apr 2022 Eric Guizzo, Tillman Weyde, Simone Scardapane, Danilo Comminiello

On the one hand, the classifier permits to optimize each latent axis of the embeddings for the classification of a specific emotion-related characteristic: valence, arousal, dominance and overall emotion.

Speech Emotion Recognition

L3DAS22 Challenge: Learning 3D Audio Sources in a Real Office Environment

1 code implementation21 Feb 2022 Eric Guizzo, Christian Marinoni, Marco Pennese, Xinlei Ren, Xiguang Zheng, Chen Zhang, Bruno Masiero, Aurelio Uncini, Danilo Comminiello

The L3DAS22 Challenge is aimed at encouraging the development of machine learning strategies for 3D speech enhancement and 3D sound localization and detection in office-like environments.

Sound Event Localization and Detection Speech Enhancement

L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing

1 code implementation12 Apr 2021 Eric Guizzo, Riccardo F. Gramaccioni, Saeid Jamili, Christian Marinoni, Edoardo Massaro, Claudia Medaglia, Giuseppe Nachira, Leonardo Nucciarelli, Ludovica Paglialunga, Marco Pennese, Sveva Pepe, Enrico Rocchi, Aurelio Uncini, Danilo Comminiello

The L3DAS21 Challenge is aimed at encouraging and fostering collaborative research on machine learning for 3D audio signal processing, with particular focus on 3D speech enhancement (SE) and 3D sound localization and detection (SELD).

Audio Signal Processing BIG-bench Machine Learning +1

Anti-Transfer Learning for Task Invariance in Convolutional Neural Networks for Speech Processing

1 code implementation11 Jun 2020 Eric Guizzo, Tillman Weyde, Giacomo Tarroni

While transfer learning assumes that the learning process for a target task will benefit from re-using representations learned for another task, anti-transfer avoids the learning of representations that have been learned for an orthogonal task, i. e., one that is not relevant and potentially misleading for the target task, such as speaker identity for speech recognition or speech content for emotion recognition.

Emotion Recognition speech-recognition +2

Multi-Time-Scale Convolution for Emotion Recognition from Speech Audio Signals

1 code implementation6 Mar 2020 Eric Guizzo, Tillman Weyde, Jack Barnett Leveson

We evaluate MTS and standard convolutional layers in different architectures for emotion recognition from speech audio, using 4 datasets of different sizes.

Emotion Recognition

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