Classical Music Generation in Distinct Dastgahs with AlimNet ACGAN
In this paper AlimNet (With respect to great musician, Alim Qasimov) an auxiliary generative adversarial deep neural network (ACGAN) for generating music categorically, is used. This proposed network is a conditional ACGAN to condition the generation process on music tracks which has a hybrid architecture, composing of different kind of layers of neural networks. The employed music dataset is MICM which contains 1137 music samples (506 violins and 631 straw) with seven types of classical music Dastgah labels. To extract both temporal and spectral features, Short-Time Fourier Transform (STFT) is applied to convert input audio signals from time domain to time-frequency domain. GANs are composed of a generator for generating new samples and a discriminator to help generator making better samples. Samples in time-frequency domain are used to train discriminator in fourteen classes (seven Dastgahs and two instruments). The outputs of the conditional ACGAN are also artificial music samples in those mentioned scales in time-frequency domain. Then the output of the generator is transformed by Inverse STFT (ISTFT). Finally, randomly ten generated music samples (five violin and five straw samples) are given to ten musicians to rate how exact the samples are and the overall result was 76.5%.
Code (0)
등록된 구현이 없습니다.
Tasks
Music GenerationSimilar Papers 제목 키워드 기반
Instrument-Independent Dastgah Recognition of Iranian Classical Music Using AzarNet
In this paper, AzarNet, a deep neural network (DNN), is proposed to recognizing seven different Dastgahs of Iranian classical music in Maryam Iranian classical music (MICM) dataset. Over the last years, there has been re…
ClassificationGeneral ClassificationRecognizing Seven Different Dastgahs Of Iranian Classical MusicExploring LLMs for South Asian Music Understanding and Generation
Recent advancements in Large Language Models (LLMs) have shown promising results in music understanding and generation tasks. However, existing works remain confined to Western tonal traditions, offering little insight i…
Music GenerationMusic ModelingIranian Modal Music (Dastgah) detection using deep neural networks
Music classification and genre detection are topics in music information retrieval (MIR) that many articles have been published regarding their utilities in the modern world. However, this contribution is insufficient in…
ArticlesInformation RetrievalMusic ClassificationMusic Information Retrieval+2Classical Music Clustering Based on Acoustic Features
In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create signature for each music piece and perfo…
ClusteringQuantum Concept Music Score from Quantum Picturalism: Musical Incarnation of a Bell-Pair under Measurements
We initiate the development of a new language and theory for quantum music, to which we refer as Quantum Concept Music (QCM). This new music formalism is based on Categorical Quantum Mechanics (CQM), and more specificall…