In this paper, we present nnAudio, a new neural network-based audio processing framework
with graphics processing unit (GPU) support that leverages 1D convolutional neural …

The estimation of fundamental frequency (F0) from audio is a necessary step in many
speech processing tasks such as speech synthesis, that require to accurately analyze big …

Automatic cover detection--the task of finding in an audio database all the covers of one or
several query tracks--has long been seen as a challenging theoretical problem in the MIR …

Extracting pitch information from music recordings is a challenging but important problem in
music signal processing. Frame-wise transcription or multi-pitch estimation aims for …

In this paper, we adapt a recently proposed U-net deep neural network architecture from
melody to bass transcription. We investigate pitch shifting and random equalization as data …

The DALI dataset is a large dataset of time-aligned symbolic vocal melody notations (notes)
and lyrics at four levels of granularity. DALI contains 5358 songs in its first version and 7756 …

Automatic cover detection-the task of finding in an audio dataset all covers of a query track-
has long been a challenging theoretical problem in MIR community. It also became a …

Recent works have addressed the automatic cover detection problem from a metric learning
perspective. They employ different input representations, aiming to exploit melodic or …

The performance of machine learning (ML) models is known to be affected by discrepancies
between training (source) and real-world (target) data distributions. This problem is referred …

Accurate voiced/unvoiced information is crucial in estimating the pitch of a target speech
signal in severe nonstationary noise environments. Nevertheless, state-of-the-art pitch …