Table 1.

Summary of the reviews used as a starting point for the present survey.

	Focus	Taxonomy	References	Mentions to creativity	Pages
Nierhaus (2009)	Broad review of all the methods for algorithmic composition in literature.	Method	328	24	294
Fernández and Vico (2013)	Broad (yet condensed) review of all the methods for algorithmic composition in literature.	Method	337	38	70
Williams et al. (2015)	Affective/emotional assessment integrated in algorithmic composition.	Expressive features	123	0	24
Herremans et al. (2017)	An objective-based taxonomy to better understand the state of the art in music generation.	Objective and method	165	4	30
Lopez-Rincon et al. (2018)	Brief introduction on a variety of AI methods used for music generation.	Method	32	2	7
Tatar and Pasquier (2019)	Generative musical agents.	Typology of agents	205	122	50
Briot et al. (2020)	Music generation using deep learning techniques.	Method	212	37	303

For each, the focus for the choice of works to be reviewed is reported, as well as what the classification of the systems is based upon (Taxonomy), the number of references present in the reviews, the number of times creativity is mentioned, and finally the page count.