Following their success in Computer Vision and other areas, deep learning techniques have
recently become widely adopted in Music Information Retrieval (MIR) research. However …

Given the recent surge in developments of deep learning, this paper provides a review of the
state-of-the-art deep learning techniques for audio signal processing. Speech, music, and …

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 …

We propose a model to estimate the fundamental frequency in monophonic audio, often
referred to as pitch estimation. We acknowledge the fact that obtaining ground truth …

In the context of automatic speech recognition and acoustic event detection, an adaptive
procedure named per-channel energy normalization (PCEN) has recently shown to …

Deep learning models have improved cutting-edge technologies in many research areas,
but their black-box structure makes it difficult to understand their inner workings and the …

Deep learning work on musical instrument recognition has generally focused on instrument
classes for which we have abundant data. In this work, we exploit hierarchical relationships …

Music genre classification, especially using lyrics alone, remains a challenging topic in
Music Information Retrieval. In this study we apply recurrent neural network models to …

The expressive variability in producing a musical note conveys information essential to the
modeling of orchestration and style. As such, it plays a crucial role in computer-assisted …

In time series classification and regression, signals are typically mapped into some
intermediate representation used for constructing models. Since the underlying task is often …