Web image search is inspired by text search techniques; it mainly relies on indexing textual data that surround the image file. But retrieval results are often noisy and image processing techniques have been proposed to rerank images. Unfortunately, these techniques usually imply a computational overload that makes the reranking process intractable in real time. We introduce here a lightweight reranking method that compares each result not only to the other query results but also to an external, contrastive class of items. The external class contains diversified images; the intuition supporting our approach is that results that are visually similar to other query results but dissimilar to elements of the contrastive class are likely to be good answers. The success of visual reranking depends on the visual coherence of queries; we measure this coherence in order to evaluate the chances of success. Visual reranking tends to emerge near duplicate images and we complement it with a diversification function which ensures that different aspects of a query are presented to the user. Our method is evaluated against a standard search engine using 210 diversified queries. Significant improvements are reported for both quantitative and qualitative tests.
Natural speech is produced by the vocal organs of a particular talker. The acoustic features of the speech signal must therefore be correlated with the movements of the articulators (lips, jaw, tongue, velum,...). For instance, hearing impaired people (and not only them) improve their understanding of speech by lip reading. This chapter is an overview of audiovisual speech processing with emphasis on some experiments concerning recognition, speaker verification, indexing and corpus based synthesis from tongue and lips movements.
Existing music search engines process music as they would process text, ignoring the richness of this media. We introduce here MuMa 1 (MUsic MAshup), a web application which makes the most of audio contents (the signal itself) to provide the user with new ways of browsing music. MuMa allows the user to search for particular chords sequences, to generate smart playlists and to extend its musical universe.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.