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

Automatic Music Transcription has seen significant progress in recent years by training
custom deep neural networks on large datasets. However, these models have required …

Most of the state-of-the-art automatic music transcription (AMT) models break down the main
transcription task into sub-tasks such as onset prediction and offset prediction and train them …

Abstract This paper presents Scene2Wav, a novel deep convolutional model proposed to
handle the task of music generation from emotionally annotated video. This is important …

Generating music with emotion similar to that of an input video is a very relevant issue
nowadays. Video content creators and automatic movie directors benefit from maintaining …

Piano transcription is a classic problem in music information retrieval. More and more
transcription methods based on deep learning have been proposed in recent years. In 2019 …

Music transcription, as an essential component in music signal processing, contributes to
wide applications in musicology, accelerates the development of commercial music industry …

The problem of automatic music transcription (AMT) is considered by many researchers as
the holy grail of the field, because of the notorious complexity and difficulty of the problem …

Audio, one of the most common sources of multimedia information in our daily life, contains
a lot of useful information to analyze. In the audio signal, an acoustic event is defined as a …

Most of the state-of-the-art automatic music transcription (AMT) models break down the main
transcription task into sub-tasks such as onset prediction and offset prediction and train them …