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The automation of guitar tablature generation from video inputs holds significant promise for enhancing music education, transcription accuracy, and performance analysis. Existing methods face challenges with consistency and completeness,…

Guitar tablatures enrich the structure of traditional music notation by assigning each note to a string and fret of a guitar in a particular tuning, indicating precisely where to play the note on the instrument. The problem of generating…

Sound · Computer Science 2024-08-12 Drew Edwards , Xavier Riley , Pedro Sarmento , Simon Dixon

A big challenge in algorithmic composition is to devise a model that is both easily trainable and able to reproduce the long-range temporal dependencies typical of music. Here we investigate how artificial neural networks can be trained on…

Machine Learning · Statistics 2016-06-24 Florian Colombo , Samuel P. Muscinelli , Alexander Seeholzer , Johanni Brea , Wulfram Gerstner

Recently, symbolic music generation with deep learning techniques has witnessed steady improvements. Most works on this topic focus on MIDI representations, but less attention has been paid to symbolic music generation using guitar…

Sound · Computer Science 2023-02-13 Pedro Sarmento , Adarsh Kumar , Yu-Hua Chen , CJ Carr , Zack Zukowski , Mathieu Barthet

Current state-of-the-art AI based classical music creation algorithms such as Music Transformer are trained by employing single sequence of notes with time-shifts. The major drawback of absolute time interval expression is the difficulty of…

Sound · Computer Science 2020-07-15 Xianchao Wu , Chengyuan Wang , Qinying Lei

Guitar tablature transcription consists in deducing the string and the fret number on which each note should be played to reproduce the actual musical part. This assignment should lead to playable string-fret combinations throughout the…

This paper presents the Jazz Transformer, a generative model that utilizes a neural sequence model called the Transformer-XL for modeling lead sheets of Jazz music. Moreover, the model endeavors to incorporate structural events present in…

Sound · Computer Science 2020-08-05 Shih-Lun Wu , Yi-Hsuan Yang

To apply neural sequence models such as the Transformers to music generation tasks, one has to represent a piece of music by a sequence of tokens drawn from a finite set of pre-defined vocabulary. Such a vocabulary usually involves tokens…

Sound · Computer Science 2021-01-08 Wen-Yi Hsiao , Jen-Yu Liu , Yin-Cheng Yeh , Yi-Hsuan Yang

Deep learning has recently empowered and democratized generative modeling of images and text, with additional concurrent works exploring the possibility of generating more complex forms of data, such as audio. However, the high…

Audio and Speech Processing · Electrical Eng. & Systems 2023-02-02 Josue Casco-Rodriguez

Automatic generation of sequences has been a highly explored field in the last years. In particular, natural language processing and automatic music composition have gained importance due to the recent advances in machine learning and…

Sound · Computer Science 2020-12-03 Sebastian Garcia-Valencia , Alejandro Betancourt , Juan G. Lalinde-Pulido

As deep learning advances, algorithms of music composition increase in performance. However, most of the successful models are designed for specific musical structures. Here, we present BachProp, an algorithmic composer that can generate…

Sound · Computer Science 2020-07-07 Florian Colombo , Johanni Brea , Wulfram Gerstner

We explore the use of neural synthesis for acoustic guitar from string-wise MIDI input. We propose four different systems and compare them with both objective metrics and subjective evaluation against natural audio and a sample-based…

Sound · Computer Science 2023-09-15 Nicolas Jonason , Xin Wang , Erica Cooper , Lauri Juvela , Bob L. T. Sturm , Junichi Yamagishi

Automatic music generation with artificial intelligence typically requires a large amount of data which is hard to obtain for many less common genres and musical instruments. To tackle this issue, we present ongoing work and preliminary…

Sound · Computer Science 2023-01-04 Li Zhang , Chris Callison-Burch

Recent work in the field of symbolic music generation has shown value in using a tokenization based on the GuitarPro format, a symbolic representation supporting guitar expressive attributes, as an input and output representation. We extend…

Sound · Computer Science 2023-07-12 Jackson Loth , Pedro Sarmento , CJ Carr , Zack Zukowski , Mathieu Barthet

This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate musical content. We propose a methodology based on five dimensions for our analysis: Objective - What musical…

Sound · Computer Science 2019-08-09 Jean-Pierre Briot , Gaëtan Hadjeres , François-David Pachet

Deep Learning models have shown very promising results in automatically composing polyphonic music pieces. However, it is very hard to control such models in order to guide the compositions towards a desired goal. We are interested in…

Machine Learning · Computer Science 2021-03-11 Lucas N. Ferreira , Jim Whitehead

Although the automatic identification of the optimal fingering for the performance of melodies on fretted string instruments has already been addressed (at least partially) in the literature, the specific case regarding lead electric guitar…

Artificial Intelligence · Computer Science 2024-07-15 Pierluigi Bontempi , Daniele Manerba , Alexandre D'Hooge , Sergio Canazza

Guitar tablature is a form of music notation widely used among guitarists. It captures not only the musical content of a piece, but also its implementation and ornamentation on the instrument. Guitar Tablature Transcription (GTT) is an…

Sound · Computer Science 2025-05-27 Yongyi Zang , Yi Zhong , Frank Cwitkowitz , Zhiyao Duan

Recent advances in deep neural networks have enabled algorithms to compose music that is comparable to music composed by humans. However, few algorithms allow the user to generate music with tunable parameters. The ability to tune…

Sound · Computer Science 2018-02-06 Huanru Henry Mao , Taylor Shin , Garrison W. Cottrell

In this paper, we propose a recurrent neural network (RNN)-based MIDI music composition machine that is able to learn musical knowledge from existing Beatles' songs and generate music in the style of the Beatles with little human…

Sound · Computer Science 2018-12-19 Yichao Zhou , Wei Chu , Sam Young , Xin Chen
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