2 citations · 2 across the 7 of their papers we have counts for
7 papers
Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition
Phuong-Anh Nguyen, The-Son Le, Duc-Trong Le +1
Multimodal Emotion Recognition in Conversations (MERC) is a crucial task for understanding human interactions, where multimodal approaches integrating language, facial expressions,…
BALM: A Model-Agnostic Framework for Balanced Multimodal Learning under Imbalanced Missing Rates
Phuong-Anh Nguyen, Tien Anh Pham, Duc-Trong Le +1
Learning from multiple modalities often suffers from imbalance, where information-rich modalities dominate optimization while weaker or partially missing modalities contribute less…
MissBench: Benchmarking Multimodal Affective Analysis under Imbalanced Missing Modalities
Tien Anh Pham, Phuong-Anh Nguyen, Duc-Trong Le +1
Multimodal affective computing underpins key tasks such as sentiment analysis and emotion recognition. Standard evaluations, however, often assume that textual, acoustic, and visua…
Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Ye Bai, Haonan Chen, Jitong Chen +35
We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regr…
StemGen: A music generation model that listens
Julian D. Parker, Janne Spijkervet, Katerina Kosta +6
End-to-end generation of musical audio using deep learning techniques has seen an explosion of activity recently. However, most models concentrate on generating fully mixed music i…
A Foundation Model for Music Informatics
Minz Won, Yun-Ning Hung, Duc Le
This paper investigates foundation models tailored for music informatics, a domain currently challenged by the scarcity of labeled data and generalization issues. To this end, we c…
Scaling Up Music Information Retrieval Training with Semi-Supervised Learning
Yun-Ning Hung, Ju-Chiang Wang, Minz Won +1
In the era of data-driven Music Information Retrieval (MIR), the scarcity of labeled data has been one of the major concerns to the success of an MIR task. In this work, we leverag…