Výsledky vyhledávání

Learning Speech Emotion Representations in the Quaternion Domain

Autor: Danilo Comminiello, Simone Scardapane, Eric Guizzo, Tillman Weyde

The modeling of human emotion expression in speech signals is an important, yet challenging task. The high resource demand of speech emotion recognition models, combined with the the general scarcity of emotion-labelled data are obstacles to the deve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::111cdc4f2a9cc569b56401aa51c2afbe

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

Autor: 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. This challenge improves and extends the tasks of the L3DAS21 e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f414cadbeeb6f713124f8bc708ad729

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L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing

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

Publikováno v: MLSP

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). Alongside with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec50eebcfec39e81ab09a30b41b64645

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Anti-transfer learning for task invariance in convolutional neural networks for speech processing

Autor: Tillman Weyde, Giacomo Tarroni, Eric Guizzo

Publikováno v: Neural Networks

We introduce the novel concept of anti-transfer learning for speech processing with convolutional neural networks. While transfer learning assumes that the learning process for a target task will benefit from re-using representations learned for anot

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78f5ab4342b5ed4028650875ab6c9173
https://pubmed.ncbi.nlm.nih.gov/34034071

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

Autor: Eric Guizzo, Jack Barnett Leveson, Tillman Weyde

Publikováno v: ICASSP

Robustness against temporal variations is important for emotion recognition from speech audio, since emotion is expressed through complex spectral patterns that can exhibit significant local dilation and compression on the time axis depending on spea

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53b5d9ff343e60b50e61f645482c28b4
https://doi.org/10.1109/icassp40776.2020.9053727

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Towards a Multimodal Time-Based Empathy Prediction System

Autor: Fermin Moscoso del Prado Martin, Giovanni Maffei, Francesco Barbieri, Federico Lucchesi, Tillman Weyde, Eric Guizzo

Publikováno v: FG

We describe our system for empathic emotion recognition. It is based on deep learning on multiple modalities in a late fusion architecture. We describe the modules of our system and discuss the evaluation results. Our code is also available for the r

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ab727d29fe98fb71eff014502b3e12e
https://doi.org/10.1109/fg.2019.8756532

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