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In this paper, we explore the tokenized representation of musical scores using the Transformer model to automatically generate musical scores. Thus far, sequence models have yielded fruitful results with note-level (MIDI-equivalent)…

声音 · 计算机科学 2021-12-02 Masahiro Suzuki

We introduce Ragas (Retrieval Augmented Generation Assessment), a framework for reference-free evaluation of Retrieval Augmented Generation (RAG) pipelines. RAG systems are composed of a retrieval and an LLM based generation module, and…

计算与语言 · 计算机科学 2025-04-29 Shahul Es , Jithin James , Luis Espinosa-Anke , Steven Schockaert

This paper introduces a new large-scale music dataset, MusicNet, to serve as a source of supervision and evaluation of machine learning methods for music research. MusicNet consists of hundreds of freely-licensed classical music recordings…

机器学习 · 统计学 2017-04-07 John Thickstun , Zaid Harchaoui , Sham Kakade

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

Music recommendation systems have emerged as a vital component to enhance user experience and satisfaction for the music streaming services, which dominates music consumption. The key challenge in improving these recommender systems lies in…

声音 · 计算机科学 2023-07-21 Junfei Zhang

In this paper, we consider the problem of probabilistically modelling symbolic music data. We introduce a representation which reduces polyphonic music to a univariate categorical sequence. In this way, we are able to apply state of the art…

声音 · 计算机科学 2016-06-07 Christian Walder

In this paper, we propose to infer music genre embeddings from audio datasets carrying semantic information about genres. We show that such embeddings can be used for disambiguating genre tags (identification of different labels for the…

信息检索 · 计算机科学 2018-09-20 Romain Hennequin , Jimena Royo-Letelier , Manuel Moussallam

In this paper, we propose a recurrent neural network (RNN) with residual attention (RRA) to learn long-range dependencies from sequential data. We propose to add residual connections across timesteps to RNN, which explicitly enhances the…

机器学习 · 计算机科学 2017-09-19 Cheng Wang

Sign language is a gesture-based symbolic communication medium among speech and hearing impaired people. It also serves as a communication bridge between non-impaired and impaired populations. Unfortunately, in most situations, a…

计算机视觉与模式识别 · 计算机科学 2025-02-19 Prasun Roy , Saumik Bhattacharya , Partha Pratim Roy , Umapada Pal

Music prediction tasks range from predicting tags given a song or clip of audio, predicting the name of the artist, or predicting related songs given a song, clip, artist name or tag. That is, we are interested in every semantic…

机器学习 · 计算机科学 2015-03-19 Jason Weston , Samy Bengio , Philippe Hamel

This paper reports a preliminary study on quantitative frequency domain rhythm cues for classifying five Indian languages: Bengali, Kannada, Malayalam, Marathi, and Tamil. We employ rhythm formant (R-formants) analysis, a technique…

音频与语音处理 · 电气工程与系统科学 2024-10-10 Parismita Gogoi , Sishir Kalita , Priyankoo Sarmah , S. R Mahadeva Prasanna

Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These algorithms take as input epigenomic datasets, such as chromatin immunoprecipitation-sequencing (ChIP-seq)…

基因组学 · 定量生物学 2022-06-14 Maxwell W Libbrecht , Rachel CW Chan , Michael M Hoffman

The integration of additional side information to improve music source separation has been investigated numerous times, e.g., by adding features to the input or by adding learning targets in a multi-task learning scenario. These approaches,…

音频与语音处理 · 电气工程与系统科学 2022-06-28 Yun-Ning Hung , Alexander Lerch

Musical mode is one of the most critical element that establishes the framework of pitch organization and determines the harmonic relationships. Previous works often use the simplistic and rigid alignment method, and overlook the diversity…

声音 · 计算机科学 2025-01-15 Qian Liang , Yi Zeng , Menghaoran Tang

Music source separation demixes a piece of music into its individual sound sources (vocals, percussion, melodic instruments, etc.), a task with no simple mathematical solution. It requires deep learning methods involving training on large…

Music autotagging aims to automatically assign descriptive tags, such as genre, mood, or instrumentation, to audio recordings. Due to its challenges, diversity of semantic descriptions, and practical value in various applications, it has…

声音 · 计算机科学 2025-09-09 Pedro Ramoneda , Pablo Alonso-Jiménez , Sergio Oramas , Xavier Serra , Dmitry Bogdanov

Music information retrieval faces a challenge in modeling contextualized musical concepts formulated by a set of co-occurring tags. In this paper, we investigate the suitability of our recently proposed approach based on a Siamese neural…

机器学习 · 计算机科学 2016-06-08 Ubai Sandouk , Ke Chen

Bangla music is enrich in its own music cultures. Now a days music genre classification is very significant because of the exponential increase in available music, both in digital and physical formats. It is necessary to index them…

声音 · 计算机科学 2026-01-22 Muntakimur Rahaman , Md Mahmudul Hoque , Md Mehedi Hassain

Many music theoretical constructs (such as scale types, modes, cadences, and chord types) are defined in terms of pitch intervals---relative distances between pitches. Therefore, when computer models are employed in music tasks, it can be…

声音 · 计算机科学 2019-02-05 Stefan Lattner , Maarten Grachten , Gerhard Widmer

The proliferation of distorted, compressed, and manipulated music on modern media platforms like TikTok motivates the development of more robust audio fingerprinting techniques to identify the sources of musical recordings. In this paper,…

声音 · 计算机科学 2025-11-10 Shubhr Singh , Kiran Bhat , Xavier Riley , Benjamin Resnick , John Thickstun , Walter De Brouwer