3 research outputs found

    PhonItalia: a phonological lexicon for Italian.

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    In this article, we present the first open-access lexical database that provides phonological representations for 120,000 Italian word forms. Each of these also includes syllable boundaries and stress markings and a comprehensive range of lexical statistics. Using data derived from this lexicon, we have also generated a set of derived databases and provided estimates of positional frequency use for Italian phonemes, syllables, syllable onsets and codas, and character and phoneme bigrams. These databases are freely available from phonitalia.org. This article describes the methods, content, and summarizing statistics for these databases. In a first application of this database, we also demonstrate how the distribution of phonological substitution errors made by Italian aphasic patients is related to phoneme frequency

    Non-hexagonal neural dynamics in vowel space

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    Are the grid cells discovered in rodents relevant to human cognition? Following up on two seminal studies by others, we aimed to check whether an approximate 6-fold, grid-like symmetry shows up in the cortical activity of humans who "navigate" between vowels, given that vowel space can be approximated with a continuous trapezoidal 2D manifold, spanned by the first and second formant frequencies. We created 30 vowel trajectories in the assumedly flat central portion of the trapezoid. Each of these trajectories had a duration of 240 milliseconds, with a steady start and end point on the perimeter of a "wheel". We hypothesized that if the neural representation of this "box" is similar to that of rodent grid units, there should be an at least partial hexagonal (6-fold) symmetry in the EEG response of participants who navigate it. We have not found any dominant n-fold symmetry, however, but instead, using PCAs, we find indications that the vowel representation may reflect phonetic features, as positioned on the vowel manifold. The suggestion, therefore, is that vowels are encoded in relation to their salient sensory-perceptual variables, and are not assigned to arbitrary gridlike abstract maps. Finally, we explored the relationship between the first PCA eigenvector and putative vowel attractors for native Italian speakers, who served as the subjects in our study
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