Towards Evaluation of Autonomously Generated Musical Compositions: A Comprehensive Survey

04/10/2022
by   daniel-kvak, et al.
0

There are many applications that aim to create a complete model for an autonomously generated composition; systems are able to generate muzak songs, assist singers in transcribing songs or can imitate long-dead authors. Subjective understanding of creativity or aesthetics differs not only within preferences (popular authors or genres), but also differs on the basis of experienced experience or socio-cultural environment. So, what do we want to achieve with such an adaptation? What is the benefit of the resulting work for the author, who can no longer evaluate this composition? And in what ways should we evaluate such a composition at all?

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/28/2022

Subjective Evaluation of Deep Learning Models for Symbolic Music Composition

Deep learning models are typically evaluated to measure and compare thei...
research
06/01/2021

Exploring Exotic Counterpoint Compositions

In this paper, first musical compositions are presented, which are creat...
research
12/09/2014

Computoser - rule-based, probability-driven algorithmic music composition

This paper presents the Computoser hybrid probability/rule based algorit...
research
10/04/2020

Creating Contexts of Creativity: Musical Composition with Modular Components

This paper describes a series of projects that explore the possibilities...
research
09/23/2022

The Beauty of Repetition in Machine Composition Scenarios

Repetition, a basic form of artistic creation, appears in most musical w...
research
08/29/2022

Quality of Experience Optimization in IoT Energy Services

We propose a novel Quality of Experience (QoE) metric as a key criterion...
research
05/17/2019

D2d -- XML for Authors

D2d is an input format which allows experienced authors to create type c...

Please sign up or login with your details

Forgot password? Click here to reset