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In music domain, feature learning has been conducted mainly in two ways: unsupervised learning based on sparse representations or supervised learning by semantic labels such as music genre. However, finding discriminative features in an…

声音 · 计算机科学 2018-06-20 Jiyoung Park , Jongpil Lee , Jangyeon Park , Jung-Woo Ha , Juhan Nam

Music contains hierarchical structures beyond beats and measures. While hierarchical structure annotations are helpful for music information retrieval and computer musicology, such annotations are scarce in current digital music databases.…

声音 · 计算机科学 2022-09-22 Junyan Jiang , Daniel Chin , Yixiao Zhang , Gus Xia

Audio representation learning based on deep neural networks (DNNs) emerged as an alternative approach to hand-crafted features. For achieving high performance, DNNs often need a large amount of annotated data which can be difficult and…

机器学习 · 计算机科学 2020-07-09 Xavier Favory , Konstantinos Drossos , Tuomas Virtanen , Xavier Serra

With the growing amount of musical data available, automatic instrument recognition, one of the essential problems in Music Information Retrieval (MIR), is drawing more and more attention. While automatic recognition of single instruments…

声音 · 计算机科学 2023-06-16 Lifan Zhong , Erica Cooper , Junichi Yamagishi , Nobuaki Minematsu

Musical pieces can be modeled as complex networks. This fosters innovative ways to categorize music, paving the way towards novel applications in multimedia domains, such as music didactics, multimedia entertainment and digital music…

信息检索 · 计算机科学 2017-09-18 Stefano Ferretti

Timbre allows us to distinguish between sounds even when they share the same pitch and loudness, playing an important role in music, instrument recognition, and speech. Traditional approaches, such as frequency analysis or machine learning,…

声音 · 计算机科学 2026-02-05 Gakusei Sato , Hiroya Nakao , Riccardo Muolo

The diversity of tables makes table detection a great challenge, leading to existing models becoming more tedious and complex. Despite achieving high performance, they often overfit to the table style in training set, and suffer from…

计算与语言 · 计算机科学 2023-12-19 Yang Fan , Xiangping Wu , Qingcai Chen , Heng Li , Yan Huang , Zhixiang Cai , Qitian Wu

We seek to develop simultaneous segmentation and classification of notes from audio recordings in presence of outliers. The selected architecture for modeling time series is hierarchical linear dynamical system (HLDS). We propose a novel…

声音 · 计算机科学 2022-03-01 Leila Kalantari , Jose Principe , Kathryn E. Sieving

Learning symbolic music representations, especially disentangled representations with probabilistic interpretations, has been shown to benefit both music understanding and generation. However, most models are only applicable to short-term…

声音 · 计算机科学 2022-02-15 Shiqi Wei , Gus Xia

This paper explores a new natural language processing task, review-driven multi-label music style classification. This task requires the system to identify multiple styles of music based on its reviews on websites. The biggest challenge…

计算与语言 · 计算机科学 2018-08-24 Guangxiang Zhao , Jingjing Xu , Qi Zeng , Xuancheng Ren

The task of labeling multiple organs for segmentation is a complex and time-consuming process, resulting in a scarcity of comprehensively labeled multi-organ datasets while the emergence of numerous partially labeled datasets. Current…

计算机视觉与模式识别 · 计算机科学 2024-07-18 Xiaoyu Liu , Linhao Qu , Ziyue Xie , Yonghong Shi , Zhijian Song

Music source separation performance has greatly improved in recent years with the advent of approaches based on deep learning. Such methods typically require large amounts of labelled training data, which in the case of music consist of…

声音 · 计算机科学 2019-09-19 Ethan Manilow , Gordon Wichern , Prem Seetharaman , Jonathan Le Roux

Music is often experienced as a progression of concurrent streams of notes, or voices. The degree to which this happens depends on the position along a voice-leading continuum, ranging from monophonic, to homophonic, to polyphonic, which…

声音 · 计算机科学 2020-11-06 Patrick Gray , Razvan Bunescu

Identifying instrument activities within audio excerpts is vital in music information retrieval, with significant implications for music cataloging and discovery. Prior deep learning endeavors in musical instrument recognition have…

Recently, automatic music transcription has made it possible to convert musical audio into accurate MIDI. However, the resulting MIDI lacks music notations such as tempo, which hinders its conversion into sheet music. In this paper, we…

音频与语音处理 · 电气工程与系统科学 2025-04-28 Zhanhong He , Roberto Togneri , Xiangyu Zhang

Recent years have witnessed the success of deep learning on the visual sound separation task. However, existing works follow similar settings where the training and testing datasets share the same musical instrument categories, which to…

多媒体 · 计算机科学 2022-03-28 Xinchi Zhou , Dongzhan Zhou , Wanli Ouyang , Hang Zhou , Ziwei Liu , Di Hu

Analyzing sequential data is crucial in many domains, particularly due to the abundance of data collected from the Internet of Things paradigm. Time series classification, the task of categorizing sequential data, has gained prominence,…

机器学习 · 计算机科学 2024-06-21 Venkata Ragavendra Vavilthota , Ranjith Ramanathan , Sathyanarayanan N. Aakur

In classical music and in any genre of contemporary music, the tonal elements or notes used for playing are the same. The numerous possibilities of chords for a given instance in a piece make the playing, in general, very intricate, and…

声音 · 计算机科学 2022-06-14 Steve Mathew D A

This paper focuses on the nominal durations of musical events (notes and rests) in a symbolic musical score, and on how to conveniently handle these in computer applications. We propose the usage of a temporal unit that is directly related…

In a setting where segmentation models have to be built for multiple datasets, each with its own corresponding label set, a straightforward way is to learn one model for every dataset and its labels. Alternatively, multi-task architectures…

计算机视觉与模式识别 · 计算机科学 2024-11-19 Deepa Anand , Bipul Das , Vyshnav Dangeti , Antony Jerald , Rakesh Mullick , Uday Patil , Pakhi Sharma , Prasad Sudhakar