Can MusicGen Create Training Data for MIR Tasks?

We are investigating the broader concept of using AI-based generative music systems to generate training data for Music Information Retrieval (MIR) tasks. To kick off this line of work, we ran an initial experiment in which we trained a genre classifier on a fully artificial music dataset created with MusicGen. We constructed over 50 000 genre- conditioned textual descriptions and generated a collection of music excerpts that covers five musical genres. Our preliminary results show that the proposed model can learn genre-specific characteristics from artificial music tracks that generalise well to real-world music recordings.Comment: This is an extended abstract presented at the Late-Breaking / Demo Session of the International Society for Music Information Retrieval Conference (ISMIR) 2023 (Milan, Italy

Detection of Melodic Patterns in Automatic Transcriptions of Flamenco Singing

The spontaneous expressive interpretation of melodic templates is a fundamental concept in flamenco music. Consequently, the automatic detection of such patterns in music collections sets the basis for a number of challenging analysis and retrieval tasks. We present a novel algorithm for the automatic detection of manually defined melodies within a corpus of automatic transcriptions of flamenco recordings. We evaluate the performance on the example of five characteristic patterns from the fandango de Valverde style and demonstrate that the algorithm is capable of retrieving ornamented instances of query patterns. Furthermore, we discuss limitations, possible extensions and applications of the proposed system

If you want to know about a hunter, study his prey: detection of network based attacks on KVM based cloud environments

Computational systems are gradually moving towards Cloud Computing Infrastructures, using the several advantages they have to offer and especially the economic advantages in the era of an economic crisis. In addition to this revolution, several security matters emerged and especially the confrontation of malicious insiders. This paper proposes a methodology for detecting the co-residency and network stressing attacks in the kernel layer of a Kvm-based cloud environment, using an implementation of the Smith-Waterman genetic algorithm. The proposed approach has been explored in a test bed environment, producing results that verify its effectiveness

Reproducible Research in Signal Processing

Reproducible research results become more and more an important issue as systems under investigation are growing permanently in complexity, and it becomes thus almost impossible to judge the accuracy of research results merely on the bare paper presentation.Peer ReviewedPreprin

Automatic Detection of Melodic Patterns in Flamenco Singing by Analyzing Polyphonic Music Recordings

In this work an analysis of characteristic melodic pattern in flamenco fandango style is carried out. Contrary to other analysis, where corpora are searched for characteristic melodic patterns, in this work characteristic melodic patterns are defined by flamenco experts and then searched in the corpora. In our case, the corpora were composed of pieces taken from two fandango styles, Valverde fandangos and Huelva capital fandangos. The chosen styles are representative of fandango styles and are also different as for their musical characteristics. The patterns provided by the flamenco experts were specified in MIDI format, but the corpora under study were provided in audio format. Two algorithms had to be designed to accomplish the goal of our research: first, an algorithm extracting audio features from the corpus and outputting a MIDI-like format; second, an algorithm to actually perform the search based on the output provided by the first algorithm. Flamenco experts assessed the results of the searches and drew conclusions

Introduction to audio analysis: a MATLAB approach

Introduction to Audio Analysis serves as a standalone introduction to audio analysis, providing theoretical background to many state-of-the-art techniques. It covers the essential theory necessary to develop audio engineering applications, but also uses programming techniques, notably MATLAB®, to take a more applied approach to the topic. Basic theory and reproducible experiments are combined to demonstrate theoretical concepts from a practical point of view and provide a solid foundation in the field of audio analysis. Audio feature extraction, audio classification, audio segmentation, a