{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T07:39:06Z","timestamp":1723016346540},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,7]]},"abstract":"<jats:p>We demonstrate a pattern-based MIDI music generation\n\nsystem with a generation strategy based on\n\nWasserstein autoencoders and a novel variant of pianoroll\n\ndescriptions of patterns which employs separate\n\nchannels for note velocities and note durations\n\nand can be fed into classic DCGAN-style convolutional\n\narchitectures. We trained the system on two\n\nnew datasets (in the acid-jazz and high-pop genres)\n\ncomposed by musicians in our team with music\n\ngeneration in mind. Our demonstration shows\n\nthat moving smoothly in the latent space allows us\n\nto generate meaningful sequences of four-bars patterns.<\/jats:p>","DOI":"10.24963\/ijcai.2020\/751","type":"proceedings-article","created":{"date-parts":[[2020,7,8]],"date-time":"2020-07-08T12:12:10Z","timestamp":1594210330000},"page":"5225-5227","source":"Crossref","is-referenced-by-count":1,"title":["Pattern-Based Music Generation with Wasserstein Autoencoders and PRC Descriptions"],"prefix":"10.24963","author":[{"given":"Valentijn","family":"Borghuis","sequence":"first","affiliation":[{"name":"Eindhoven University of Technology"}]},{"given":"Luca","family":"Angioloni","sequence":"additional","affiliation":[{"name":"University of Florence"}]},{"given":"Lorenzo","family":"Brusci","sequence":"additional","affiliation":[{"name":"Musica Combinatoria (Musi-Co)"}]},{"given":"Paolo","family":"Frasconi","sequence":"additional","affiliation":[{"name":"University of Florence"}]}],"member":"10584","event":{"number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-PRICAI-2020","name":"Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}","start":{"date-parts":[[2020,7,11]]},"theme":"Artificial Intelligence","location":"Yokohama, Japan","end":{"date-parts":[[2020,7,17]]}},"container-title":["Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T02:17:01Z","timestamp":1594261021000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2020\/751"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2020,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2020\/751","relation":{},"subject":[],"published":{"date-parts":[[2020,7]]}}}