Browsing School of Electronic Engineering and Computer Science by Author "Gyenge, N"
Now showing items 1-4 of 4
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Large-Scale Pretrained Model for Self-Supervised Music Audio Representation Learning
Li, Y; Yuan, R; Zhang, G; Ma, Y; Lin, C; Chen, X; Ragni, A; Yin, H; Hu, Z; He, H (2022-12-20)Self-supervised learning technique is an under-explored topic for music audio due to the challenge of designing an appropriate training paradigm. We hence propose MAP-MERT, a large-scale music audio pre-trained model for ... -
MARBLE: Music Audio Representation Benchmark for Universal Evaluation
Yuan, R; Ma, Y; Li, Y; Zhang, G; Chen, X; Yin, H; Zhuo, L; Liu, Y; Huang, J; Tian, Z (37th Conference on Neural Information Processing Systems (NeurIPS), 2023)In the era of extensive intersection between art and Artificial Intelligence (AI), such as image generation and fiction co-creation, AI for music remains relatively nascent, particularly in music understanding. This is ... -
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
Li, Y; Yuan, R; Zhang, G; Ma, Y; Chen, X; Yin, H; Xiao, C; Lin, C; Ragni, A; Benetos, E (2024-05-07)Self-supervised learning (SSL) has recently emerged as a promising paradigm for training generalisable models on large-scale data in the fields of vision, text, and speech. Although SSL has been proven effective in speech ... -
On the effectiveness of speech self-supervised learning for music
Ma, Y; Yuan, R; Li, Y; Zhang, G; Chen, X; Yin, H; Lin, C; Benetos, E; Ragni, A; Gyenge, N (International Society for Music Information Retrieval Conference (ISMIR), 2023-11-05)Self-supervised learning (SSL) has shown promising results in various speech and natural language processing applications. However, its efficacy in music information retrieval (MIR) still remains largely unexplored. While ...