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20202026
most citedMERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

28 citations · 52 across the 23 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.SD2023

MERTech: Instrument Playing Technique Detection Using Self-Supervised Pretrained Model With Multi-Task Finetuning

Dichucheng Li, Yinghao Ma, Weixing Wei +6

Instrument playing techniques (IPTs) constitute a pivotal component of musical expression. However, the development of automatic IPT detection methods suffers from limited labeled…

eess.AS2023

MusiLingo: Bridging Music and Text with Pre-trained Language Models for Music Captioning and Query Response

Zihao Deng, Yinghao Ma, Yudong Liu +5

Large Language Models (LLMs) have shown immense potential in multimodal applications, yet the convergence of textual and musical domains remains not well-explored. To address this…

cs.SD2023★ 2 cited

On the Effectiveness of Speech Self-supervised Learning for Music

Yinghao Ma, Ruibin Yuan, Yizhi Li +12

Self-supervised learning (SSL) has shown promising results in various speech and natural language processing applications. However, its efficacy in music information retrieval (MIR…

cs.CL2023★ 3 cited

LyricWhiz: Robust Multilingual Zero-shot Lyrics Transcription by Whispering to ChatGPT

Le Zhuo, Ruibin Yuan, Jiahao Pan +10

We introduce LyricWhiz, a robust, multilingual, and zero-shot automatic lyrics transcription method achieving state-of-the-art performance on various lyrics transcription datasets,…

cs.SD2023★ 6 cited

MARBLE: Music Audio Representation Benchmark for Universal Evaluation

Ruibin Yuan, Yinghao Ma, Yizhi Li +22

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, partic…

cs.SD2023★ 28 cited

MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

Yizhi Li, Ruibin Yuan, Ge Zhang +17

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. Althoug…