175 citations · 243 across the 15 of their papers we have counts for
15 papers
Music Era Recognition Using Supervised Contrastive Learning and Artist Information
Qiqi He, Xuchen Song, Weituo Hao +3
Does popular music from the 60s sound different than that of the 90s? Prior study has shown that there would exist some variations of patterns and regularities related to instrumen…
InstructME: An Instruction Guided Music Edit And Remix Framework with Latent Diffusion Models
Bing Han, Junyu Dai, Weituo Hao +6
Music editing primarily entails the modification of instrument tracks or remixing in the whole, which offers a novel reinterpretation of the original piece through a series of oper…
Efficient Neural Music Generation
Max W. Y. Lam, Qiao Tian, Tang Li +10
Recent progress in music generation has been remarkably advanced by the state-of-the-art MusicLM, which comprises a hierarchy of three LMs, respectively, for semantic, coarse acous…
ALCAP: Alignment-Augmented Music Captioner
Zihao He, Weituo Hao, Wei-Tsung Lu +3
Music captioning has gained significant attention in the wake of the rising prominence of streaming media platforms. Traditional approaches often prioritize either the audio or lyr…
Modeling Beats and Downbeats with a Time-Frequency Transformer
Yun-Ning Hung, Ju-Chiang Wang, Xuchen Song +2
Transformer is a successful deep neural network (DNN) architecture that has shown its versatility not only in natural language processing but also in music information retrieval (M…
SpecTNT: a Time-Frequency Transformer for Music Audio
Wei-Tsung Lu, Ju-Chiang Wang, Minz Won +2
Transformers have drawn attention in the MIR field for their remarkable performance shown in natural language processing and computer vision. However, prior works in the audio proc…
Supervised Metric Learning for Music Structure Features
Ju-Chiang Wang, Jordan B. L. Smith, Wei-Tsung Lu +1
Music structure analysis (MSA) methods traditionally search for musically meaningful patterns in audio: homogeneity, repetition, novelty, and segment-length regularity. Hand-crafte…
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection
Yingjie Zhou, Xucheng Song, Yanru Zhang +3
Weakly-supervised anomaly detection aims at learning an anomaly detector from a limited amount of labeled data and abundant unlabeled data. Recent works build deep neural networks…
Supervised Chorus Detection for Popular Music Using Convolutional Neural Network and Multi-task Learning
Ju-Chiang Wang, Jordan B. L. Smith, Jitong Chen +2
This paper presents a novel supervised approach to detecting the chorus segments in popular music. Traditional approaches to this task are mostly unsupervised, with pipelines desig…
Modeling the Compatibility of Stem Tracks to Generate Music Mashups
Jiawen Huang, Ju-Chiang Wang, Jordan B. L. Smith +2
A music mashup combines audio elements from two or more songs to create a new work. To reduce the time and effort required to make them, researchers have developed algorithms that…
CatNet: music source separation system with mix-audio augmentation
Xuchen Song, Qiuqiang Kong, Xingjian Du +1
Music source separation (MSS) is the task of separating a music piece into individual sources, such as vocals and accompaniment. Recently, neural network based methods have been ap…
High-resolution Piano Transcription with Pedals by Regressing Onset and Offset Times
Qiuqiang Kong, Bochen Li, Xuchen Song +2
Automatic music transcription (AMT) is the task of transcribing audio recordings into symbolic representations. Recently, neural network-based methods have been applied to AMT, and…
Noise Robust TTS for Low Resource Speakers using Pre-trained Model and Speech Enhancement
Dongyang Dai, Li Chen, Yuping Wang +5
With the popularity of deep neural network, speech synthesis task has achieved significant improvements based on the end-to-end encoder-decoder framework in the recent days. More a…
Source separation with weakly labelled data: An approach to computational auditory scene analysis
Qiuqiang Kong, Yuxuan Wang, Xuchen Song +3
Source separation is the task to separate an audio recording into individual sound sources. Source separation is fundamental for computational auditory scene analysis. Previous wor…
Deep Anomaly Detection in Packet Payload
Jiaxin Liu, Xucheng Song, Yingjie Zhou +4
With the widespread adoption of cloud services, especially the extensive deployment of plenty of Web applications, it is important and challenging to detect anomalies from the pack…