Abdellah Fourtassi

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We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding zero resource (unsupervised) speech technologies and related models of early language acquisition. Centered around the tasks of phonetic and lexical discovery, we consider unified evaluation metrics, present two new approaches for(More)
Evaluation methods for Distributional Semantic Models typically rely on behaviorally derived gold standards. These methods are difficult to deploy in languages with scarce linguistic/behavioral resources. We introduce a corpus-based measure that evaluates the stability of the lexical semantic similarity space using a pseudo-synonym same-different detection(More)
Infants spontaneously discover the relevant phonemes of their language without any direct supervision. This acquisition is puzzling because it seems to require the availability of high levels of linguistic structures (lexicon, semantics), that logically suppose the infants having a set of phonemes already. We show how this circularity can be broken by(More)
We test both bottom-up and top-down approaches in learning the phonemic status of the sounds of English and Japanese. We used large corpora of spontaneous speech to provide the learner with an input that models both the linguistic properties and statistical regularities of each language. We found both approaches to help discriminate between allophonic and(More)
In this paper we introduce an inductive bias for language acquisition under a view where learning of the various levels of linguistic structure takes place interactively. The bias encourages the learner to choose sound systems that lead to more “semantically coherent” lexicons. We quantify this coherence using an intrinsic and unsupervised measure of(More)
Cross-linguistic studies on unsupervised word segmentation have consistently shown that English is easier to segment than other languages. In this paper, we propose an explanation of this finding based on the notion of segmentation ambiguity. We show that English has a very low segmentation ambiguity compared to Japanese and that this difference correlates(More)
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