The discipline of Deep Learning has been recognized for its strong computational tools,
which have been extensively used in data and signal processing, with innumerable …

Data-driven models for audio source separation such as U-Net or Wave-U-Net are usually
models dedicated to and specifically trained for a single task, eg a particular instrument …

Multitrack music transcription aims to transcribe a music audio input into the musical notes of
multiple instruments simultaneously. It is a very challenging task that typically requires a …

La séparation de sources sonores consiste à extraire une ou plusieurs sources présentant
un attrait significatif d'un enregistrement contenant plusieurs sources sonores. Ces …

In many situations, we would like to hear desired sound events (SEs) while being able to
ignore interference. Target sound extraction (TSE) tackles this problem by estimating the …

Recently, the time-domain-based methods (ie, the method of modeling the raw waveform
directly) for audio source separation have shown tremendous potential. In this paper, we …

Humans have devised a vast array of musical instruments, but the most prevalent instrument
remains the human voice. Thus, techniques for applying audio signal processing methods to …

This paper provides a guide through the FMP notebooks, a comprehensive collection of
educational material for teaching and learning fundamentals of music processing (FMP) with …

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 …

Stacked dilated convolutions used in Wavenet have been shown effective for generating
high-quality audios. By replacing pooling/striding with dilation in convolution layers, they can …