Titlebook: Computational Intelligence in Music, Sound, Art and Design; 6th International Co João Correia,Vic Ciesielski,Antonios Liapis Conference pro

手术刀

Play it Again: Evolved Audio Effects and Synthesizer Programming,urs) and solution accuracy, based on particularities of the target devices. Random oscillators, phase synchronizing, and filters over empty frequency ranges are identified as primary challenges for GA based optimization.

态学

https://doi.org/10.1007/978-3-8349-8010-6uss its success at pitch and rhythm prediction. Next, we show how ALYSIA was used to create original pop songs that were subsequently recorded and produced. Finally, we discuss our vision for the future of Automated Songwriting for both co-creative and autonomous systems.

思想流动

Wolfgang Lassmann,Andreas Lassmannhallenges is conforming human intuitive perception and what we perceive as aesthetically pleasing with the output of a computational model. Informational theories of aesthetics have taken advantage of entropy in measuring order and complexity of stimuli in relation to their aesthetic value. However

Engulf

Kathrin M. Möslein,Emilio E. Matthaeineous voices, errors of duration or position can lead to badly aligned and inharmonious digital transcriptions. We adapt biological sequence analysis tools as a post-processing step to correct the alignment of voices. Our multiple sequence alignment approach works on multiple musical dimensions and

Peculate

Wolfgang Lassmann,Andreas Lassmannwo music documents. In the context of symbolically encoded melodies, pairwise alignment via dynamic programming has been the most widely used method. However, this approach fails to scale-up well in terms of time complexity and insufficiently models the variance between melodies of the same class. C

推崇

Lukasz Gadowski,Michael Petersenf mapping expressions. When given an artistic input these mapping expressions can be used to guide the generation of content in a separate domain. For example, a piece of music can be used to create an analogous visual display. In this paper we examine the implementation and performance of such a sy

无法破译

https://doi.org/10.1007/978-981-13-0800-0icial Composer (DAC), a recurrent neural network model of note transitions for the automated composition of melodies. Our model can be trained to produce melodies with compositional structures extracted from large datasets of diverse styles of music, which we exemplify here on a corpus of Irish folk

阻塞

https://doi.org/10.1007/978-981-13-0800-0sk in this area is the automatic recognition of musical styles. The style of a music performer is the result of the combination of several factors such as experience, personality, preferences, especially in music genres where the improvisation plays an important role..In this paper we propose a new

悲痛

Tatiana B. Agranat,Leyli R. Dodykhudoevaarmony agent employs a Long Short-Term Memory (LSTM) artificial neural network trained on the chord progressions of 2986 jazz ‘standard’ compositions using a network structure novel to chord sequence analysis. The melody agent uses a rule-based system of manipulating provided, pre-composed melodies

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