Melody extraction algorithms aim to produce a sequence of frequency values corresponding
to the pitch of the dominant melody from a musical recording. Over the past decade, melody …

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

Popular music is often composed of an accompaniment and a lead component, the latter
typically consisting of vocals. Filtering such mixtures to extract one or both components has …

Singing melody extraction essentially involves two tasks: one is detecting the activity of a
singing voice in polyphonic music, and the other is estimating the pitch of a singing voice in …

In this paper, we propose a new method for singing voice detection based on a Bidirectional
Long Short-Term Memory (BLSTM) Recurrent Neural Network (RNN). This classifier is able …

Singing pitch estimation and singing voice separation are challenging due to the presence
of music accompaniments that are often nonstationary and harmonic. Inspired by …

Predominant instrument recognition in ensemble recordings remains a challenging task,
particularly if closelyrelated instruments such as alto and tenor saxophone need to be …

This paper presents a system for the transcription of singing voice melodies in polyphonic
music signals based on Deep Neural Network (DNN) models. In particular, a new DNN …

Vocal melody extraction is an important and challenging task in music information retrieval.
One main difficulty is that, most of the time, various instruments and singing voices are mixed …

Separating singing voice from music accompaniment can be of interest for many
applications such as melody extraction, singer identification, lyrics alignment and …