Audio segmentation-by-classification approach based on factor analysis in broadcast news domain

作者：Castan Diego^*; Ortega Alfonso; Miguel Antonio; Lleida Eduardo

来源：EURASIP Journal on Audio Speech and Music Processing, 2014, 2014(1): 34.

DOI：10.1186/s13636-014-0034-5

• Audio segmentation
• Factor analysis
• Within-class variability compensation
• Broadcast news
• Albayzin 2010 evaluation

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.

• 出版日期2014-8-28