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We propose an algorithm for the blind separation of single-channel audio signals. It is based on a parametric model that describes the spectral properties of the sounds of musical instruments independently of pitch. We develop a novel…

Audio and Speech Processing · Electrical Eng. & Systems 2021-02-03 Sören Schulze , Emily J. King

While many topics of the learning-based approach to automated music generation are under active research, musical form is under-researched. In particular, recent methods based on deep learning models generate music that, at the largest time…

Sound · Computer Science 2024-04-19 Lilac Atassi

This work addresses the problem of matching short excerpts of audio with their respective counterparts in sheet music images. We show how to employ neural network-based cross-modality embedding spaces for solving the following two sheet…

Information Retrieval · Computer Science 2017-08-01 Matthias Dorfer , Andreas Arzt , Gerhard Widmer

We provide a justification for why, and when, endogeneity will not cause bias in the interpretation of the coefficients in a regression model. This technique can be a viable alternative to, or even used alongside, the instrumental variable…

General Economics · Economics 2022-03-29 Ravi Kashyap

Audio-to-score alignment aims at generating an accurate mapping between a performance audio and the score of a given piece. Standard alignment methods are based on Dynamic Time Warping (DTW) and employ handcrafted features, which cannot be…

Sound · Computer Science 2020-11-17 Ruchit Agrawal , Simon Dixon

Existing methods for expressive music performance rendering rely on supervised learning over small labeled datasets, which limits scaling of both data volume and model size, despite the availability of vast unlabeled music, as in vision and…

Sound · Computer Science 2025-12-03 Hong-Jie You , Jie-Jing Shao , Xiao-Wen Yang , Lin-Han Jia , Lan-Zhe Guo , Yu-Feng Li

We develop a multidimensional version of Gradient-MUSIC for estimating the frequencies of a nonharmonic signal from noisy samples. The guiding principle is that frequency recovery should be based only on the signal subspace determined by…

Optimization and Control · Mathematics 2026-03-31 Albert Fannjiang , Weilin Li

This paper presents a new approach to algorithmic composition, called predictive controlled music (PCM), which combines model predictive control (MPC) with music generation. PCM uses dynamic models to predict and optimize the music…

Sound · Computer Science 2026-01-09 Midhun T. Augustine

The criteria for measuring music similarity are important for developing a flexible music recommendation system. Some data-driven methods have been proposed to calculate music similarity from only music signals, such as metric learning…

Sound · Computer Science 2022-11-16 Yuka Hashizume , Li Li , Tomoki Toda

The tabla is a unique percussion instrument due to the combined harmonic and percussive nature of its timbre, and the contrasting harmonic frequency ranges of its two drums. This allows a tabla player to uniquely emphasize parts of the…

Audio and Speech Processing · Electrical Eng. & Systems 2021-04-20 Rohit M. A. , Preeti Rao

The transduction process that occurs in the inner ear of the auditory system is a complex mechanism which requires a non-linear dynamical description. In addition to this, the stochastic phenomena that naturally arise in the inner ear…

Physics Education · Physics 2022-01-17 Francesco Veronesi , Edoardo Milotti

Creativity, or the ability to produce new useful ideas, is commonly associated to the human being; but there are many other examples in nature where this phenomenon can be observed. Inspired by this fact, in engineering and particularly in…

Sound · Computer Science 2022-01-26 David Daniel Albarracín Molina

Multi-instrument music transcription aims to convert polyphonic music recordings into musical scores assigned to each instrument. This task is challenging for modeling as it requires simultaneously identifying multiple instruments and…

Audio and Speech Processing · Electrical Eng. & Systems 2024-08-02 Sungkyun Chang , Emmanouil Benetos , Holger Kirchhoff , Simon Dixon

We propose a method for the problem of real time chord accompaniment of improvised music. Our implementation can learn an underlying structure of the musical performance and predict next chord. The system uses Hidden Markov Model to find…

Human-Computer Interaction · Computer Science 2012-06-28 Panagiotis Tigas

This application-oriented study concerns computational musicology, which makes use of grammar systems. We define multi-generative rule-synchronized scattered-context grammar systems (without erasing rules) and demonstrates how to…

Formal Languages and Automata Theory · Computer Science 2025-07-22 Jozef Makiš , Alexander Meduna , Zbyněk Křivka

Recent work has proposed training machine learning models to predict aesthetic ratings for music audio. Our work explores whether such models can be used to finetune a symbolic music generation system with reinforcement learning, and what…

Sound · Computer Science 2025-04-24 Nicolas Jonason , Luca Casini , Bob L. T. Sturm

This paper proposes a polynomial-time algorithm to construct the monotone stepwise curve that minimizes the sum of squared errors with respect to a given cloud of data points. The fitted curve is also constrained on the maximum number of…

Optimization and Control · Mathematics 2021-07-01 Víctor Bucarey , Martine Labbé , Juan M. Morales , Salvador Pineda

Many music AI models learn a map between music content and human-defined labels. However, many annotations, such as chords, can be naturally expressed within the music modality itself, e.g., as sequences of symbolic notes. This observation…

Sound · Computer Science 2025-09-30 Junyan Jiang , Daniel Chin , Liwei Lin , Xuanjie Liu , Gus Xia

FM Synthesis is a well-known algorithm used to generate complex timbre from a compact set of design primitives. Typically featuring a MIDI interface, it is usually impractical to control it from an audio source. On the other hand,…

Sound · Computer Science 2022-08-15 Franco Caspe , Andrew McPherson , Mark Sandler

The quality of outputs produced by deep generative models for music have seen a dramatic improvement in the last few years. However, most deep learning models perform in "offline" mode, with few restrictions on the processing time.…

Sound · Computer Science 2019-05-01 Pablo Samuel Castro
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