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The largest source of sound events is web videos. Most videos lack soundevent labels at segment level, however, a significant number of them do respondto text queries, from a match found using metadata by search engines. In thispaper we explore the extent to which a search query can be used as the truelabel for detection of sound events in videos. We present a framework forlarge-scale sound event recognition on web videos. The framework crawls videosusing search queries corresponding to 78 sound event labels drawn from threedatasets. The datasets are used to train three classifiers, and we obtain aprediction on 3.7 million web video segments. We evaluated performance usingthe search query as true label and compare it with human labeling. Both typesof ground truth exhibited close performance, to within 10%, and similarperformance trend with increasing number of evaluated segments. Hence, ourexperiments show potential for using search query as a preliminary true labelfor sound event recognition in web videos.

Framework for evaluation of sound event detection in web videos