Endowing machines with sensing capabilities similar to those of humans is a prevalent
quest in engineering and computer science. In the pursuit of making computers sense their …

Music information retrieval (MIR) is an emerging research area that receives growing
attention from both the research community and music industry. It addresses the problem of …

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 …

A huge increase in the number of digital music tracks has created the necessity to develop
an automated tool to extract the useful information from these tracks. As this information has …

Audio feature extraction and classification are important tools for audio signal analysis in
many applications, such as multimedia indexing and retrieval, and auditory scene analysis …

In tackling data mining and pattern recognition tasks, finding a compact but effective set of
features has often been found to be a crucial step in the overall problem-solving process. In …

Cochlear implants (CIs) have been remarkably successful at restoring hearing in severely-to-
profoundly hearing-impaired individuals. However, users often struggle to deconstruct …

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 …

Nonnegative matrix factorization (NMF) is used to derive a novel description for the timbre of
musical sounds. Using NMF, a spectrogram is factorized providing a characteristic spectral …

In a musical signals, the spectral and temporal contents of instruments often overlap. If the
number of channels is at least the same as the number of instruments, it is possible to apply …