33 citations · 34 across the 4 of their papers we have counts for
4 papers
Unsupervised Improvement of Audio-Text Cross-Modal Representations
Zhepei Wang, Cem Subakan, Krishna Subramani +4
Recent advances in using language models to obtain cross-modal audio-text representations have overcome the limitations of conventional training approaches that use predefined labe…
Segment Relevance Estimation for Audio Analysis and Weakly-Labelled Classification
Juliano Henrique Foleiss, Tiago Fernandes Tavares
We propose a method that quantifies the importance, namely relevance, of audio segments for classification in weakly-labelled problems. It works by drawing information from a set o…
Random Projections of Mel-Spectrograms as Low-Level Features for Automatic Music Genre Classification
Juliano Henrique Foleiss, Tiago Fernandes Tavares
In this work, we analyse the random projections of Mel-spectrograms as low-level features for music genre classification. This approach was compared to handcrafted features, featur…
Texture Selection for Automatic Music Genre Classification
Juliano H. Foleiss, Tiago F. Tavares
Music Genre Classification is the problem of associating genre-related labels to digitized music tracks. It has applications in the organization of commercial and personal music co…