2 citations · 3 across the 4 of their papers we have counts for
4 papers
EmotionRankCLAP: Bridging Natural Language Speaking Styles and Ordinal Speech Emotion via Rank-N-Contrast
Shreeram Suresh Chandra, Lucas Goncalves, Junchen Lu +2
Current emotion-based contrastive language-audio pretraining (CLAP) methods typically learn by naïvely aligning audio samples with corresponding text prompts. Consequently, this ap…
Improving Lip-synchrony in Direct Audio-Visual Speech-to-Speech Translation
Lucas Goncalves, Prashant Mathur, Xing Niu +5
Audio-Visual Speech-to-Speech Translation typically prioritizes improving translation quality and naturalness. However, an equally critical aspect in audio-visual content is lip-sy…
PEAVS: Perceptual Evaluation of Audio-Visual Synchrony Grounded in Viewers' Opinion Scores
Lucas Goncalves, Prashant Mathur, Chandrashekhar Lavania +3
Recent advancements in audio-visual generative modeling have been propelled by progress in deep learning and the availability of data-rich benchmarks. However, the growth is not at…
EMO-SUPERB: An In-depth Look at Speech Emotion Recognition
Haibin Wu, Huang-Cheng Chou, Kai-Wei Chang +5
Speech emotion recognition (SER) is a pivotal technology for human-computer interaction systems. However, 80.77% of SER papers yield results that cannot be reproduced. We develop E…