Simon Petit-Renaud

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In most statistical machine translation (SMT) systems, bilingual segments are extracted via word alignment. However, there is a need for systematic study as to what alignment characteristics can benefit MT under specific experimental settings such as the type of MT system, the language pair or the type or size of the corpus. In this paper we perform, in(More)
—In this paper, we present HAMEX, a new public dataset that contains mathematical expressions available in their on-line handwritten form and in their audio spoken form. We have designed this dataset so that, given a mathematical expression, its handwritten signal and its audio signal can be used jointly to design multimodal recognition systems. Here, we(More)
In this paper, we consider the extraction of speaker identity from audio records of broadcast news without a priori acoustic information about speakers. Using an automatic speech recognition system and an automatic speaker diariza-tion system, we present improvements for a method which allows to extract speaker identities from automatic transcripts and to(More)
—Considerable efforts are being done within the scientific community to make as easier as possible the way that the human being converses with its machine. Handwriting and speech are two common ways used to achieve this goal and are probably among those which attracted much interest. In mathematical content recognition tasks, these two modalities are used(More)
In this paper, we consider the issue of speaker identification within audio records of broadcast news. The speaker identity information is extracted from both transcript-based and acoustic-based speaker identification systems. This information is combined in the belief functions framework, which makes coherent the knowledge representation of the problem.(More)
We propose a new approach to functional regression based on fuzzy evidence theory. This method uses a training set for computing a fuzzy belief structure which quantiies diierent types of uncertainties, such as nonspeciicity, connict, or low density of input data. The method can cope with a very large class of training data, such as numbers, intervals ,(More)
The main goal of this work is to set up a multimodal system dedicated to mathematical expression recognition. In the proposed architecture, the transcription coming out from a speech recognition system is used to disambiguate the result of a handwriting recognition module. A set of keywords is built from the transcription module and used to rescore the(More)