Deep CNN Framework for Audio Event Recognition using Weakly Labeled Web Data

The development of audio event recognition models requires labeled training data, which are generally hard to obtain. One promising source of recordings of audio events is the large amount of multimedia data on the web. In particular, if the audio content analysis must itself be performed on web audio, it is important to train the recognizers themselves from such data. Training from these web data, however, poses several challenges, the most important being the availability of labels : labels, if any, that may be obtained for the data are generally {\em weak}, and not of the kind conventionally required for training detectors or classifiers. We propose that learning algorithms that can exploit weak labels offer an effective method to learn from web data. We then propose a robust and efficient deep convolutional neural network (CNN) based framework to learn audio event recognizers from weakly labeled data. The proposed method can train from and analyze recordings of variable length in an efficient manner and outperforms a network trained with {\em strongly labeled} web data by a considerable margin

How a "Hit" is Born: The Emergence of Popularity from the Dynamics of Collective Choice

In recent times there has been a surge of interest in seeking out patterns in the aggregate behavior of socio-economic systems. One such domain is the emergence of statistical regularities in the evolution of collective choice from individual behavior. This is manifested in the sudden emergence of popularity or "success" of certain ideas or products, compared to their numerous, often very similar, competitors. In this paper, we present an empirical study of a wide range of popularity distributions, spanning from scientific paper citations to movie gross income. Our results show that in the majority of cases, the distribution follows a log-normal form, suggesting that multiplicative stochastic processes are the basis for emergence of popular entities. This suggests the existence of some general principles of complex organization leading to the emergence of popularity. We discuss the theoretical principles needed to explain this socio-economic phenomenon, and present a model for collective behavior that exhibits bimodality, which has been observed in certain empirical popularity distributions.Comment: 17 pages, 14 figures, A version of the work is published in Econophysics and Sociophysics: Trends and Perspectives, (eds.) Bikas K. Chakrabarti, Anirban Chakraborti, Arnab Chatterjee; Wiley-VCH, Berlin (2006); Chapter-15, pages: 417-44