Computational Creativity is a multidisciplinary field that tries to obtain creative behaviors
from computers. One of its most prolific subfields is that of Music Generation (also called …

We propose Diffusion Inference-Time T-Optimization (DITTO), a general-purpose frame-
work for controlling pre-trained text-to-music diffusion models at inference-time via …

Deep learning technology has been extensively studied for its potential in music, notably for
creative music generation research. Traditional music generation approaches based on …

For successful artificial music composition, chords and melody must be aligned well. Yet,
chord conditioned melody generation remains a challenging task mainly due to its …

In music, the interpreter manipulates the performance parameters in order to offer a sonic
rendition of the piece that is capable of conveying specific expressive intentions. Since the …

Artificial intelligence, particularly machine learning, has begun to permeate various real-
world applications and is continually being explored in automatic music generation. The …

Machine learning is widely used in various practical applications with deep learning models
demonstrating advantages in handling huge data. Treating music as a special language and …

We propose a method for computing the similarity of symbolically-encoded Portuguese folk
melodies. The main novelty of our method is the use of a preprocessing melodic reduction at …

We address the problem of scalable content-based search in large collections of music
documents. Music content is highly complex and versatile and presents multiple facets that …

Making music with others is both an artistic act and a social activity. Music therapists can
leverage the social aspects of music to increase the well-being of their patients by …