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Audio segmentation is important as a pre-processing task to improve the performance of many speech technology tasks and, therefore, it has an undoubted research interest. This paper describes the database, the metric, the systems and the results for the Albayzín-2014 audio segmentation campaign. In contrast to previous evaluations where the task was the segmentation of non-overlapping classes, Albayzín-2014...
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...
This paper proposes a novel audio segmentation-by-classification system based on Factor Analysis (FA) with a channel compensation matrix for each class and scoring the fixed-length segments as the log-likelihood ratio between class/no-class. The scores are smoothed and the most probable sequence is computed with a Viterbi algorithm. The system described here is designed to segment and classify the...
Because of the popularity of online videos, there has been much interest in recent years in audio processing for the improvement of online video search. In this paper, we explore using acoustic concepts and spoken concepts extracted via audio segmentation/recognition and speech recognition respectively for Multimedia Event Detection (MED). To extract spoken concepts, a segmenter trained on annotated...
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