Audio segmentation-by-classification approach based on factor analysis in broadcast news domain
Resumen: This paper studies a novel audio segmentation-by-classification approach based on factor analysis. The proposed technique compensates the within-class variability by using class-dependent factor loading matrices and obtains the scores by computing the log-likelihood ratio for the class model to a non-class model over fixed-length windows. Afterwards, these scores are smoothed to yield longer contiguous segments of the same class by means of different back-end systems. Unlike previous solutions, our proposal does not make use of specific acoustic features and does not need a hierarchical structure. The proposed method is applied to segment and classify audios coming from TV shows into five different acoustic classes: speech, music, speech with music, speech with noise, and others. The technique is compared to a hierarchical system with specific acoustic features achieving a significant error reduction.
Idioma: Inglés
DOI: 10.1186/s13636-014-0034-5
Año: 2014
Publicado en: EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING 2014, 1 (2014), 1-13
ISSN: 1687-4714

Factor impacto JCR: 0.386 (2014)
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 213 / 247 = 0.862 (2014) - Q4 - T3
Categ. JCR: ACOUSTICS rank: 28 / 30 = 0.933 (2014) - Q4 - T3

Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2011-28169-C05-02
Tipo y forma: Article (Published version)
Área (Departamento): Teoría de la Señal y Comunicaciones (Departamento de Ingeniería Electrónica y Comunicaciones)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


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