Search Results for author: Xin Jing

Found 6 papers, 1 papers with code

STAA-Net: A Sparse and Transferable Adversarial Attack for Speech Emotion Recognition

no code implementations2 Feb 2024 Yi Chang, Zhao Ren, Zixing Zhang, Xin Jing, Kun Qian, Xi Shao, Bin Hu, Tanja Schultz, Björn W. Schuller

Speech contains rich information on the emotions of humans, and Speech Emotion Recognition (SER) has been an important topic in the area of human-computer interaction.

Adversarial Attack Speech Emotion Recognition

Dynamic Restrained Uncertainty Weighting Loss for Multitask Learning of Vocal Expression

no code implementations22 Jun 2022 Meishu Song, Zijiang Yang, Andreas Triantafyllopoulos, Xin Jing, Vincent Karas, Xie Jiangjian, Zixing Zhang, Yamamoto Yoshiharu, Bjoern W. Schuller

We propose a novel Dynamic Restrained Uncertainty Weighting Loss to experimentally handle the problem of balancing the contributions of multiple tasks on the ICML ExVo 2022 Challenge.

Exploring speaker enrolment for few-shot personalisation in emotional vocalisation prediction

1 code implementation14 Jun 2022 Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang, Xin Jing, Björn W. Schuller

In this work, we explore a novel few-shot personalisation architecture for emotional vocalisation prediction.

A Temporal-oriented Broadcast ResNet for COVID-19 Detection

no code implementations31 Mar 2022 Xin Jing, Shuo Liu, Emilia Parada-Cabaleiro, Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang, Björn W. Schuller

Detecting COVID-19 from audio signals, such as breathing and coughing, can be used as a fast and efficient pre-testing method to reduce the virus transmission.

Computational Efficiency

An Overview & Analysis of Sequence-to-Sequence Emotional Voice Conversion

no code implementations29 Mar 2022 Zijiang Yang, Xin Jing, Andreas Triantafyllopoulos, Meishu Song, Ilhan Aslan, Björn W. Schuller

Emotional voice conversion (EVC) focuses on converting a speech utterance from a source to a target emotion; it can thus be a key enabling technology for human-computer interaction applications and beyond.

Voice Conversion

Audio Self-supervised Learning: A Survey

no code implementations2 Mar 2022 Shuo Liu, Adria Mallol-Ragolta, Emilia Parada-Cabeleiro, Kun Qian, Xin Jing, Alexander Kathan, Bin Hu, Bjoern W. Schuller

Inspired by the humans' cognitive ability to generalise knowledge and skills, Self-Supervised Learning (SSL) targets at discovering general representations from large-scale data without requiring human annotations, which is an expensive and time consuming task.

Self-Supervised Learning

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