26 citations · 87 across the 8 of their papers we have counts for
5 papers · 1 filter
Towards Deep Modeling of Music Semantics using EEG Regularizers
Francisco Raposo, David Martins de Matos, Ricardo Ribeiro +2
Modeling of music audio semantics has been previously tackled through learning of mappings from audio data to high-level tags or latent unsupervised spaces. The resulting semantic…
Deep Cross-Modal Correlation Learning for Audio and Lyrics in Music Retrieval
Yi Yu, Suhua Tang, Francisco Raposo +1
Little research focuses on cross-modal correlation learning where temporal structures of different data modalities such as audio and lyrics are taken into account. Stemming from th…
An Information-theoretic Approach to Machine-oriented Music Summarization
Francisco Raposo, David Martins de Matos, Ricardo Ribeiro
Music summarization allows for higher efficiency in processing, storage, and sharing of datasets. Machine-oriented approaches, being agnostic to human consumption, optimize these a…
Using Generic Summarization to Improve Music Information Retrieval Tasks
Francisco Raposo, Ricardo Ribeiro, David Martins de Matos
In order to satisfy processing time constraints, many MIR tasks process only a segment of the whole music signal. This practice may lead to decreasing performance, since the most i…
On the Application of Generic Summarization Algorithms to Music
Francisco Raposo, Ricardo Ribeiro, David Martins de Matos
Several generic summarization algorithms were developed in the past and successfully applied in fields such as text and speech summarization. In this paper, we review and apply the…