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Alice Baird

3 accepted papers

2023

Large-Scale Nonverbal Vocalization Detection Using Transformers

Panagiotis Tzirakis, Alice Baird, Jeffrey A. Brooks, Christopher Gagne, Lauren Kim, Michael Opara +7
ICASSP 2023accepted

Detecting emotionally expressive nonverbal vocalizations is essential to developing technologies that can converse fluently with humans. The affective computing community has largely focused on understanding the intonation of emotional speech and language. However, advances in the study of vocal emo…

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2020

Generating and Protecting Against Adversarial Attacks for Deep Speech-Based Emotion Recognition Models

Zhao Ren, Alice Baird, Jing Han, Zixing Zhang, Björn W. Schuller
ICASSP 2020accepted

The development of deep learning models for speech emotion recognition has become a popular area of research. Adversarially generated data can cause false predictions, and in an endeavor to ensure model robustness, defense methods against such attacks should be addressed. With this in mind, in this…

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2020

Stargan for Emotional Speech Conversion: Validated by Data Augmentation of End-To-End Emotion Recognition

Georgios Rizos, Alice Baird, Max Elliott, Björn W. Schuller
ICASSP 2020accepted

In this paper, we propose an adversarial network implementation for speech emotion conversion as a data augmentation method, validated by a multi-class speech affect recognition task. In our setting, we do not assume the availability of parallel data, and we additionally make it a priority to exploi…

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