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Deep Learning Techniques for Music Generation – A Survey [article]

Jean-Pierre Briot, Gaëtan Hadjeres, François-David Pachet
2019 arXiv   pre-print
This paper is a survey and an analysis of different ways of using deep learning (deep artificial neural networks) to generate musical content.  ...  This typology is bottom-up, based on the analysis of many existing deep-learning based systems for music generation selected from the relevant literature.  ...  Deep Learning The motivation for using deep learning (and more generally machine learning techniques) to generate musical content is its generality.  ... 
arXiv:1709.01620v4 fatcat:hma4znleorfpvh62cpupxu4fq4

The emergence of deep learning: new opportunities for music and audio technologies

Dorien Herremans, Ching-Hua Chuan
2019 Neural computing & applications (Print)  
: • deep learning for computational music research; • modeling hierarchical and long-term music structures using deep learning; • modeling ambiguity and preference in music; • applications of deep networks  ...  There has been tremendous interest in deep learning across many fields of study. Recently, these techniques have gained popularity in the field of music.  ... 
doi:10.1007/s00521-019-04166-0 fatcat:dnzm6oamz5avhhohy3fqt477gu

Neural networks in art, sound and design

Juan Romero, Penousal Machado
2020 Neural computing & applications (Print)  
Jean-Pierre Briot, co-author of the book ''Deep Learning Techniques for Music Generation,'' describes, in a pedagogical way, several innovative proposals for the generation of music through ANNs and deep  ...  Jialin Liu et al. analyze the deep learning revolution through two converging trends in the last years: the increasing use of deep learning techniques-such as generative adversarial network, variational  ... 
doi:10.1007/s00521-020-05444-y fatcat:aszni43uo5cenf5jurlmxvbnaa

Applications of Computational Intelligence in Computer Music Composition

Nermin Siphocly, Abdel-Badeeh Salem, El-Sayed El-Horabty
2021 International Journal of Intelligent Computing and Information Sciences  
Deep neural networks are clever at capturing temporal information of a musical piece. The state-of-the-art generative adversarial networks produce music as close as possible to real compositions.  ...  Its main objective is to survey various computational intelligence techniques for performing miscellaneous music composition tasks.  ...  For example, the deep learning improvement technique proposed in [42] with the aim of reducing the error rate using auto encoder and GA can be applied in enhancing deep learning in music composition  ... 
doi:10.21608/ijicis.2021.62820.1060 fatcat:oy7fx6f5wrcyrjvav5gtwnze5y

Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners [article]

Emilia Gómez and Merlijn Blaauw and Jordi Bonada and Pritish Chandna and Helena Cuesta
2018 arXiv   pre-print
This paper summarizes some recent advances on a set of tasks related to the processing of singing using state-of-the-art deep learning techniques.  ...  However, recent data-driven machine learning techniques, specially deep learning, have substantially boosted the quality and accuracy of singing processing techniques.  ...  In this paper, we illustrate recent advances in deep learning techniques for the analysis, processing and synthesis of singing, comparing them with alternative approaches.  ... 
arXiv:1807.03046v1 fatcat:gp7ir3ea2rdyza7os2ocpn3x2m

ISMIR 2019 tutorial: waveform-based music processing with deep learning

Jongpil Lee, Jordi Pons, Sander Dieleman
2019 Zenodo  
recent advent of deep learning.  ...  A common practice when processing music signals with deep learning is to transform the raw waveform input into a time-frequency representation.  ...  "Deep learning for audio-based music classification and tagging", IEEE Signal Processing Magazine. Humphrey et al., 2013.  ... 
doi:10.5281/zenodo.3529713 fatcat:hlfuuuaexfh7zirjnprhgwnzxa

The Classification of Music and Art Genres under the Visual Threshold of Deep Learning

Zhiqiang Zheng, Vijay Kumar
2022 Computational Intelligence and Neuroscience  
This paper aims to develop a novel deep learning-enabled music genre classification (DLE-MGC) technique.  ...  In recent times, deep learning (DL) models have been widely used due to their characteristics of automatic extracting advanced features and contextual representation from actual music or processed data  ...  An audio feature such as MFCCs is generally used to input a machine learning classifier in classical techniques, such as neural networks and deep neural networks [15] .  ... 
doi:10.1155/2022/4439738 pmid:35634048 pmcid:PMC9132639 fatcat:m7sz3sj3tfbbnm6dro2qfbmque

A Survey of State-of-the-art: Deep Learning Methods on Recommender System

Basiliyos Tilahun, Charles Awono, Bernabe Batchakui
2017 International Journal of Computer Applications  
In this paper different traditional recommendation techniques, deep learning approaches for recommender system and survey of deep learning techniques on recommender system are presented.  ...  Due to the limitation of the traditional recommendation methods in obtaining accurate result a deep learning approach is introduced both for collaborative and content based approaches that will enable  ...  Architectures of Deep Learning Depending on how the architectures and techniques are intended for use deep learning can be categorized in to Generative deep architectures, which are intended to characterize  ... 
doi:10.5120/ijca2017913361 fatcat:txeaquy5dfdelezsly4g7ze3ca

Exploring the Role of Deep Learning Technology in the Sustainable Development of the Music Production Industry

Sung-Shun Weng, Hung-Chia Chen
2020 Sustainability  
This study explores the role of deep learning technology in the sustainable development of the music production industry.  ...  We found that deep learning cannot replace human creativity, but greater investment in this technology can improve the quality of music creation.  ...  As this study revealed, deep learning is significantly related to techniques and capabilities for music production.  ... 
doi:10.3390/su12020625 fatcat:xmqelk4pknh4vjicmad52uzqdq

Machine listening intelligence [article]

C.E. Cella
2017 arXiv   pre-print
This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational  ...  On the contrary, deep learning proved to be valuable in incredibly different domains and showed that some learning techniques are indeed general.  ...  More recently, the uprise of deep learning techniques in computer vision created a real revolution in machine learning given the advancements they provided [Krizhevsky et al., 2012] .  ... 
arXiv:1706.09557v1 fatcat:u5zgrhrp7rcsbiuw7eufuflpxu

Music Information Retrieval and Contemporary Classical Music: A Successful Failure

Carmine-Emanuele Cella
2020 Transactions of the International Society for Music Information Retrieval  
This paper is about the story of my relationship, as a contemporary music composer, with computational tools that are situated in the areas of signal processing, machine learning and music information  ...  Finally, I will propose new possible directions for the future of MIR.  ...  Humphrey et al. (2015) presented an important overview of deep learning techniques for music informatics.  ... 
doi:10.5334/tismir.55 fatcat:rvytyjyozjf4jkeqnad6h5cyye

Musical instrument emotion recognition using deep recurrent neural network

Sangeetha Rajesh, N J Nalini
2020 Procedia Computer Science  
In this paper, a novel approach is proposed to recognize the emotion by classes of musical instruments using deep learning techniques.  ...  In this paper, a novel approach is proposed to recognize the emotion by classes of musical instruments using deep learning techniques.  ...  Traditional machine learning technique SVM and deep learning technique RNN are employed to train the extracted features.  ... 
doi:10.1016/j.procs.2020.03.178 fatcat:rd5sfk7qujfofcd6yprgqywfhu

Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening

Leonardo Gabrielli, György Fazekas, Juhan Nam
2021 Applied Sciences  
The recent introduction of Deep Learning has led to a vast array of breakthroughs in many fields of science and engineering [...]  ...  A review of Deep Learning techniques for Acoustic Scene Classification is provided by Abeßer [3] .  ...  Deep Learning for Applications in Acoustics The topics covered by the published papers cover sound synthesis, generative music, spatial audio, bioacoustics, audio scene classification and more.  ... 
doi:10.3390/app11020473 fatcat:obsm7zqddrbrhfjmlkaxdcjjsi

Special Issue on "Sound and Music Computing"

Tapio Lokki, Meinard Müller, Stefania Serafin, Vesa Välimäki
2018 Applied Sciences  
Machine and Deep Learning Deep learning is a hot topic also in sound and music computing. In this special issue, there are several articles applying deep learning techniques to various problems.  ...  [6] describes an automatic music transcription algorithm combining deep learning and spectrogram factorization techniques.  ... 
doi:10.3390/app8040518 fatcat:o2ke6272sjatladeb4dg2qypcm

Music Genre Classification Using Deep Learning Techniques

M.K.N. Haq
2021 International Journal for Research in Applied Science and Engineering Technology  
The artistic nature of music means that these classifications are often biased and notorious and some genres may overlap. We will classify the various music genres by using deep learning algorithm.  ...  Music can be divided into genres in varying ways such as into popular music and art music,hip hop music or religious music and secular music.  ...  RESULTS Fig 1.Training and validation accuracy of VGG transfer learning VI. CONCLUSION We have done the music genre classification using CNN deep learning Technique.  ... 
doi:10.22214/ijraset.2021.35965 fatcat:bhq4piksjzaebffjnt7gq3nq74
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