Work

Exploring Song Segmentation for Music Emotion Variation Detection

Year: 2024

Type: conference-paper

Abstract: This paper evaluates the impact of song segmentation on Music Emotion Variation Detection (MEVD). In particular, the All-In-One song-structure segmentation system was employed to this end and compared to a fixed 1.5-sec window approach. Acoustic features were extracted for each obtained segment/window, which were classified with SVMs. The attained results (best F1-score of 55.9%) suggest that, despite its promise, the potential of this song segmentation approach was not fully exploited, possibly due to the small employed dataset. Nevertheless, preliminary results are encouraging.

Source: Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)

Authors: Ferreira, Tomas, Redinho, Hugo, Louro, Pedro L., Malheiro, Ricardo, Paiva, Rui Pedro, Panda, Renato

Institutions: University of Coimbra, Universidade de Leiria e Oeste, Universidade Politécnica de Tomar

Language: English

Topic: Music and Audio Processing

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Programa Operacional Regional do Centro, Fundação para a Ciência e a Tecnologia

Awards: G4811366021, Reconhecimento de Emoções na Música - Próxima Geração, G6997658380, Centro de Investigação em Cidades Inteligentes, G7445779836, G7974842525

OpenAlex ID: W7019136239

FWCI:

Cites:

Cited by:

Related to: