IMT Institutional Repository: No conditions. Results ordered -Date Deposited. 2024-03-29T01:22:06ZEPrintshttp://eprints.imtlucca.it/images/logowhite.pnghttp://eprints.imtlucca.it/2017-06-21T13:17:10Z2017-06-21T13:17:10Zhttp://eprints.imtlucca.it/id/eprint/3714This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/37142017-06-21T13:17:10ZIn favor of the phonemic principle: a review of neurophysiological and neuroimaging explorations into the neural correlates of phonological competenceIn the last thirty years, in vivo brain structural and functional exploration has sparked vivid light on the neural correlates of language. Along these lines, the study of phono- logical competence has offered a ‘neural view’ into the organization of basic speech- sensitive areas, improving the sensitivity of pre-surgical mapping and brain-computer interface-based communication. Nevertheless, only rarely the significance of these results has been recognized in the context of a century-long discussion around the theoretical, physical and cognitive consistency of the phoneme itself. Here we review recent investigations into speech perception, imagery and production at the segmen- tal level through neuroimaging and neurophysiological techniques, showing that phonemes are processed as discrete entities, which are categorized in cognition as unique products of their acoustic and articulatory features, despite the seamless flow of the speech signal. These results seem to expand the scope of the motor theory of speech perception.Alessandra Cecilia Rampininialessandra.rampinini@imtlucca.itEmiliano Ricciardiemiliano.ricciardi@imtlucca.it2015-06-08T13:10:45Z2015-06-08T13:10:45Zhttp://eprints.imtlucca.it/id/eprint/2701This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/27012015-06-08T13:10:45ZInteractions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions Wikipedia is a huge global repository of human knowledge that can be leveraged to investigate interwinements between cultures. With this aim, we apply methods of Markov chains and Google matrix for the analysis of the hyperlink networks of 24 Wikipedia language editions, and rank all their articles by PageRank, 2DRank and CheiRank algorithms. Using automatic extraction of people names, we obtain the top 100 historical figures, for each edition and for each algorithm. We investigate their spatial, temporal, and gender distributions in dependence of their cultural origins. Our study demonstrates not only the existence of skewness with local figures, mainly recognized only in their own cultures, but also the existence of global historical figures appearing in a large number of editions. By determining the birth time and place of these persons, we perform an analysis of the evolution of such figures through 35 centuries of human history for each language, thus recovering interactions and entanglement of cultures over time. We also obtain the distributions of historical figures over world countries, highlighting geographical aspects of cross-cultural links. Considering historical figures who appear in multiple editions as interactions between cultures, we construct a network of cultures and identify the most influential cultures according to this network.Young-Ho Eomyoungho.eom@imtlucca.itPablo AragónDavid LaniadoAndreas KaltenbrunnerSebastiano VignaDima L. Shepelyansky2013-11-05T11:14:58Z2013-11-05T11:14:58Zhttp://eprints.imtlucca.it/id/eprint/1856This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/18562013-11-05T11:14:58ZBlock Orthonormal Overcomplete Dictionary LearningIn the field of sparse representations, the overcomplete dictionary learning problem is of crucial importance and has a growing application pool where it is used. In this paper we present an iterative dictionary learning algorithm based on the singular value decomposition that efficiently construct unions of orthonormal bases. The important innovation described in this paper, that affects positively the running time of the learning procedures, is the way in which the sparse representations are computed - data are reconstructed in a single orthonormal base, avoiding slow sparse approximation algorithms - how the bases in the union are used and updated individually and how the union itself is expanded by looking at the worst reconstructed data items. The numerical experiments show conclusively the speedup induced by our method when compared to previous works, for the same target representation
error.Cristian Rusucristian.rusu@imtlucca.itBogdan Dumitrescu2012-04-02T07:22:55Z2012-04-02T07:22:55Zhttp://eprints.imtlucca.it/id/eprint/1253This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/12532012-04-02T07:22:55ZStatistical Laws Governing Fluctuations in Word Use from Word Birth to Word DeathWe analyze the dynamic properties of 107 words recorded in English, Spanish and Hebrew over the period 1800–2008 in order to gain insight into the coevolution of language and culture. We report language independent patterns useful as benchmarks for theoretical models of language evolution. A significantly decreasing (increasing) trend in the birth (death) rate of words indicates a recent shift in the selection laws governing word use. For new words, we observe a peak in the growth-rate fluctuations around 40 years after introduction, consistent with the typical entry time into standard dictionaries and the human generational
timescale. Pronounced changes in the dynamics of language during periods of war shows that word correlations, occurring across time and between words, are largely influenced by coevolutionary social,technological, and political factors. We quantify cultural memory by analyzing the long-term correlations in the use of individual words using detrended fluctuation analysis.Alexander M. Petersenalexander.petersen@imtlucca.itJoel TenenbaumShlomo HavlinH. Eugene Stanley2012-02-01T13:17:52Z2013-11-21T09:07:26Zhttp://eprints.imtlucca.it/id/eprint/1099This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/10992012-02-01T13:17:52ZSpectral methods cluster words of the same class in a syntactic dependency networkWe analyze here a particular kind of linguistic network where vertices represent words and edges stand for syntactic relationships between words. The statistical properties of these networks have been recently studied and various features such as the small-world phenomenon and a scale-free distribution of degrees have been found. Our work focuses on four classes of words: verbs, nouns, adverbs and adjectives. Here, we use spectral methods sorting vertices. We show that the ordering clusters words of the same class. For nouns and verbs, the cluster size distribution clearly follows a power-law distribution that cannot be explained by a null hypothesis. Long-range correlations are found between vertices in the ordering provided by the spectral method. The findings support the use of spectral methods for detecting community structure.Ramon Ferrer I CanchoAndrea CapocciGuido Caldarelliguido.caldarelli@imtlucca.it