Binaural Acoustic Scene Classification Using Wavelet Scattering, Parallel Ensemble Classifiers and Nonlinear Fusion

• Tipo: Artigo em Revista Científica Internacional
• Data: 2022-02

Autores

Vahid Hajihashemi (Autor) Outra; Abdorreza Alavi Gharahbagh (Autor) Outra; Pedro Miguel Cruz (Autor) Outra; Marta Campos Ferreira (Autor) FEUP; José J. M. Machado (Autor) FEUP; João Manuel R. S. Tavares (Autor) FEUP

Revista

Título: Sensors

Vol. 22 Nº 4

Páginas: 1-19

ISSN: 1424-3210

Editora: MDPI

Indexação

ISI Web of Knowledge - 3 Citações

ISI Web of Science

Scopus - 3 Citações

Classificação Científica

CORDIS: Ciências Tecnológicas

FOS: Ciências da engenharia e tecnologias

Projetos Associados

Safe Cities - Safe Cities - Inovação para Construir Cidades Seguras

Outras Informações

ID Authenticus: P-00W-3MH

DOI: 10.3390/s22041535

Abstract (EN): The analysis of ambient sounds can be very useful when developing sound base intelligent systems. Acoustic scene classification (ASC) is defined as identifying the area of a recorded sound or clip among some predefined scenes. ASC has huge potential to be used in urban sound event classification systems. This research presents a hybrid method that includes a novel mathematical fusion step which aims to tackle the challenges of ASC accuracy and adaptability of current state-of-the-art models. The proposed method uses a stereo signal, two ensemble classifiers (random subspace), and a novel mathematical fusion step. In the proposed method, a stable, invariant signal representation of the stereo signal is built using Wavelet Scattering Transform (WST). For each mono, i.e., left and right, channel, a different random subspace classifier is trained using WST. A novel mathematical formula for fusion step was developed, its parameters being found using a Genetic algorithm. The results on the DCASE 2017 dataset showed that the proposed method has higher classification accuracy (about 95%), pushing the boundaries of existing methods.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 19