In recent years, foundation models (FMs) such as large language models (LLMs) and latent
diffusion models (LDMs) have profoundly impacted diverse sectors, including music. This …

The goal of singing voice separation is to recover the vocals signal from music mixtures.
State-of-the-art performance is achieved by deep neural networks trained in a supervised …

Singing, the vocal productionof musical tones, is one of the most important elements of
music. Addressing the needs of real-world applications, the study of technologies related to …

This paper makes several contributions to automatic lyrics transcription (ALT) research. Our
main contribution is a novel variant of the Multistreaming Time-Delay Neural Network …

Phoneme-to-audio alignment is the task of synchronizing voice recordings and their related
phonetic transcripts. In this work, we introduce a new system to forced phonetic alignment …

Lyrics alignment in long music recordings can be memory exhaustive when performed in a
single pass. In this study, we present a novel method that performs audio-to-lyrics alignment …

Lyrics alignment gained considerable attention in recent years. State-of-the-art systems
either re-use established speech recognition toolkits, or design end-to-end solutions …

Connectionist Temporal Classification (CTC) has become a standard for deep learning-
based temporal alignment allowing relevant probabilistic distributions to be learned …

In recent years, the accuracy of automatic lyrics alignment methods has increased
considerably. Yet, many current approaches employ frameworks designed for automatic …

This paper deals with a score–audio music retrieval task where the aim is to find relevant
audio recordings of Western classical music, given a short monophonic musical theme in …