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Publications associées (6)

Maya Codical Glyph Segmentation: A Crowdsourcing Approach

Daniel Gatica-Perez, Jean-Marc Odobez, Gülcan Can

This paper focuses on the crowd-annotation of an ancient Maya glyph dataset derived from the three ancient codices that survived up to date. More precisely, non-expert annotators are asked to segment glyph-blocks into their constituent glyph entities. As a ...

2018

On Modeling the Synergy Between Acoustic and Lexical Information for Pronunciation Lexicon Development

Marzieh Razavi

State-of-the-art automatic speech recognition (ASR) and text-to-speech systems require a pronunciation lexicon that maps each word to a sequence of phones. Manual development of lexicons is costly as it needs linguistic knowledge and human expertise. To fa ...

EPFL2017

Acoustic data-driven grapheme-to-phoneme conversion in the probabilistic lexical modeling framework

Mathew Magimai Doss, Marzieh Razavi, Ramya Rasipuram

One of the primary steps in building automatic speech recognition (ASR) and text-to-speech systems is the development of a phonemic lexicon that provides a mapping between each word and its pronunciation as a sequence of phonemes. Phoneme lexicons can be d ...

2016

On Learning Grapheme-to-Phoneme Relationships through the Acoustic Speech Signal

Mathew Magimai Doss, Ramya Rasipuram

Automatic speech recognition (ASR) systems, through use of the phoneme as an intermediary unit representation, split the problem of modeling the relationship between the written form, i.e., the text and the acoustic speech signal into two disjoint processe ...

2014

Grapheme-based Automatic Speech Recognition using Probabilistic Lexical Modeling

Ramya Rasipuram

Automatic speech recognition (ASR) systems incorporate expert knowledge of language or the linguistic expertise through the use of phone pronunciation lexicon (or dictionary) where each word is associated with a sequence of phones. The creation of phone pr ...

EPFL2014

Sparsity Averaging for Compressive Imaging

Jean-Philippe Thiran, Dimitri Nestor Alice Van De Ville, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

We discuss a novel sparsity prior for compressive imaging in the context of the theory of compressed sensing with coherent redundant dictionaries, based on the observation that natural images exhibit strong average sparsity over multiple coherent frames. W ...

IEEE Institute of Electrical and Electronics Engineers2013