The role of phonology in the inflection of Italian verbs

2006 ◽  
Vol 1 (1) ◽  
pp. 147-181 ◽  
Author(s):  
Lucia Colombo ◽  
Ivilin Stoianov ◽  
Margherita Pasini ◽  
Marco Zorzi

We investigated the performance of two connectionist neural networks with different architectures to explore the degree of learning in generating the past participle form of Italian verbs on the basis of phonological characteristics. The networks were trained to generate the past participle form of verbs from different inflected input forms. We examined the degree of learning relative to the type of inflection given as input, the type of suffix produced, the classification of each verb according to the thematic vowel, the regularity of the stem and of the suffix. The networks were able to learn both regular and irregular forms, but the effect of regularity depended on the distributional properties of the conjugation to which a verb belongs, and on information provided by the input.

2020 ◽  
Vol 4 (6) ◽  
pp. 139-147
Author(s):  
Marjona Akhmadovna Radjabova ◽  

Abstract. The following article discusses the role of onomastic components in phraseological units and their meaning as well as giving a classification of onomastic components in phraseological units based on the materials of different structural languages. Through examples the author proves that the presence of names in the ancient rich phraseological layer of non-fraternal English, Russian and Uzbek languages is related to the national and cultural values, customs, ancient history, folklore and daily life of the peoples who speak this language. Besides, in the process of study of onomastic components it is also determined that names, along with forming their national character, are a factor giving information about the past of a particular nation. Background. In the world linguistics there have been carried out a series of researches in the field of the study of phraseological units with onomastic components in comparative-typological aspect revaling their national and cultural peculiarities, analyzing and classifying their content structurally and semantically


2021 ◽  
Vol 13 (3-2) ◽  
pp. 410-425
Author(s):  
Denis Ignatyev ◽  
◽  
Anastasia Nikiforova ◽  

The article is devoted to the study of the problem of alienation of culture in a modern museum and the processes of actualization of objects and phenomena of history in the space of the paramuseum. In the center of the author’s attention is the theme of creating the illusion of existential comfort. It explores the contradiction between the need for museification of culture in order for a modern person to be able to appeal to it when building one’s own identity, and the constant desire to place the culture of the past on a safe reservation. The issue of aestheticization of cultural objects in the museum space and the role of a museum in interpreting, preserving and distorting their meaning is raised. The museum, created as a repository of antiquities, a collection of masterpieces, today has become the most sensitive system that responds to changes in the life of culture and society. An axiological analysis of modern museums shows their growing popularity as an element of the entertainment industry, while their aesthetic, analytical, and intellectual role is becoming obscure. Respect for the museum as a keeper of cultural memory, for the focus of scientific life is disappearing. Instead, a simplified “attraction museum” and paramuseum is coming to the fore, creating endless games with historical objects, reconstructions, visitors and interpretations of the events of history and culture. The authors of the article are among the first to turn to the concept of “paramuseum” and give it a comprehensive assessment. For the first time, a scientific classification of paramuseums (on the example of paramuseums of northwestern Russia) is proposed. Their main features and characteristics are identified. A synergistic approach to the processes of actualization and alienation of cultural objects in the museum environment made it possible to include the viewer, the recipient, as the third, necessary component of this system. This made it possible to conclude that museum values are alienated or updated not by themselves, but only in relation to the “person watching.” Thus, modern museums and paramuseums are a form of value-based self-consciousness of society, demonstrating the total stratification of post-culture society, its fragmentation into value clusters that can represent culture as a whole only in the process of analytical consciousness, but not in the collection of subject series.


2019 ◽  
Vol 72 (2) ◽  
pp. 245-272
Author(s):  
Letizia Vezzosi

Abstract Aldred’s interlinear glosses added to the Latin text of the Lindisfarne Gospels have undoubtedly an inestimable value as one of the most substantial representatives of late Old Northumbrian. Therefore, they have been an object of study both as a source of information on this Old English variety and on the typological changes affecting Middle English. Starting from the assumption that glosses have an ancillary function with respect to the Latin text they accompany, I have argued in the present paper that they can make a significant contribution to delineating the history and meaning of a word inasmuch as glossators could have chosen vernacular words according to their core meaning. The particular case of the verbs of possession āgan and the forms derived from it, including the past participle āgen, will be used in the following discussion of the role of glosses: the investigation of their meaning in the Lindisfarne Gospels will help us understand the development of āgen into the PDE attributive intensifier own.


1984 ◽  
Vol 21 (2) ◽  
pp. 155-169 ◽  
Author(s):  
Paul E. Green

Over the past few years hybrid models for conjoint analysis have been developed to reduce data collection effort and time. Hybrid models combine features of self-explicated utility measurement with more traditional conjoint analysis. A classification of hybrid models is presented, followed by a review of their comparative performance in cross-validation tests. Though hybrid models represent an attempt to cope with an important practical problem in industry applications of conjoint techniques, these models entail a number of untested assumptions requiring further theoretical analysis and empirical research. Suggestions are offered on future studies that are essential before the role of hybrid models in conjoint methods can be evaluated properly.


2021 ◽  
Author(s):  
Travis Coan ◽  
Constantine Boussalis ◽  
John Cook ◽  
Mirjam Nanko

A growing body of scholarship investigates the role of misinformation in shaping the debate on climate change. Our research builds on and extends this literature by 1) developing and validating a comprehensive taxonomy of climate misinformation, 2) conducting the largest content analysis to date on contrarian claims, 3) developing a computational model to accurately detect specific claims, and 4) drawing on an extensive corpus from conservative think-tank (CTTs) websites and contrarian blogs to construct a detailed history of misinformation over the past 20 years. Our study finds that climate misinformation produced by CTTs and contrarian blogs has focused on attacking the integrity of climate science and scientists and, increasingly, has challenged climate policy and renewable energy. We further demonstrate the utility of our approach by exploring the influence of corporate and foundation funding on the production and dissemination of specific contrarian claims.


2018 ◽  
Vol 63 (1) ◽  
pp. 139-159
Author(s):  
Isabel Repiso

The present article shows that the most frequent way of translating Should have + Past participle in Spanish is the word-by-word translation Debería haber. This preference is not coherent with the language use of natives at three levels: (i) the marginal role of modal verbs to express the speaker’s subjectivity in Spanish; (ii) the preferred use of modal verbs in the past participle position (e.g., No hubiese debido tener libros); and (iii) the predominant use of the pluperfect subjunctive as a prompting tense for counterfactual readings. Our survey is based on 1.7  million-word Social Sciences corpus covering 8 essays, 4 political biographies and 2 dystopian novels. In all, 9  sentences containing should have + past participle were analyzed. The translations were crossed with a reference corpus in Spanish containing 154 million words (CREA). The translators’ preference by Debería haber has an effect in the output texts’ readability since it implies a reversal in the frequencies of the Spanish constructions pertaining to the irrealis semantic domain. Our results provide empirical cues to prevent the word-by-word translation Debería haber, such as avoiding infinitive periphrastic constructions or favoring subjunctive mood’s tenses.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Travis G. Coan ◽  
Constantine Boussalis ◽  
John Cook ◽  
Mirjam O. Nanko

AbstractA growing body of scholarship investigates the role of misinformation in shaping the debate on climate change. Our research builds on and extends this literature by (1) developing and validating a comprehensive taxonomy of climate contrarianism, (2) conducting the largest content analysis to date on contrarian claims, (3) developing a computational model to accurately classify specific claims, and (4) drawing on an extensive corpus from conservative think-tank (CTTs) websites and contrarian blogs to construct a detailed history of claims over the past 20 years. Our study finds that the claims utilized by CTTs and contrarian blogs have focused on attacking the integrity of climate science and scientists and, increasingly, has challenged climate policy and renewable energy. We further demonstrate the utility of our approach by exploring the influence of corporate and foundation funding on the production and dissemination of specific contrarian claims.


2021 ◽  
Vol 11 (4) ◽  
pp. 1573
Author(s):  
Amin Alqudah ◽  
Ali Mohammad Alqudah ◽  
Hiam Alquran ◽  
Hussein R. Al-Zoubi ◽  
Mohammed Al-Qodah ◽  
...  

Arabic and Hindi handwritten numeral detection and classification is one of the most popular fields in the automation research. It has many applications in different fields. Automatic detection and automatic classification of handwritten numerals have persistently received attention from researchers around the world due to the robotic revolution in the past decades. Therefore, many great efforts and contributions have been made to provide highly accurate detection and classification methodologies with high performance. In this paper, we propose a two-stage methodology for the detection and classification of Arabic and Hindi handwritten numerals. The classification was based on convolutional neural networks (CNNs). The first stage of the methodology is the detection of the input numeral to be either Arabic or Hindi. The second stage is to detect the input numeral according to the language it came from. The simulation results show very high performance; the recognition rate was close to 100%.


2018 ◽  
Vol 6 ◽  
pp. 651-665 ◽  
Author(s):  
Christo Kirov ◽  
Ryan Cotterell

Can advances in NLP help advance cognitive modeling? We examine the role of artificial neural networks, the current state of the art in many common NLP tasks, by returning to a classic case study. In 1986, Rumelhart and McClelland famously introduced a neural architecture that learned to transduce English verb stems to their past tense forms. Shortly thereafter in 1988, Pinker and Prince presented a comprehensive rebuttal of many of Rumelhart and McClelland’s claims. Much of the force of their attack centered on the empirical inadequacy of the Rumelhart and McClelland model. Today, however, that model is severely outmoded. We show that the Encoder-Decoder network architectures used in modern NLP systems obviate most of Pinker and Prince’s criticisms without requiring any simplification of the past tense mapping problem. We suggest that the empirical performance of modern networks warrants a reexamination of their utility in linguistic and cognitive modeling.


Author(s):  
Changshun Du ◽  
Lei Huang

Text classification is one of the principal tasks of machine learning. It aims to design proper algorithms to enable computers to extract features and classify texts automatically. In the past, this has been mainly based on the classification of keywords and neural network semantic synthesis classification. The former emphasizes the role of keywords, while the latter focuses on the combination of words between roles. The method proposed in this paper considers the advantages of both methods. It uses an attention mechanism to learn weighting for each word. Under the setting, key words will have a higher weight, and common words will have lower weight. Therefore, the representation of texts not only considers all words, but also pays more attention to key words. Then we feed the feature vector to a softmax classifier. At last, we conduct experiments on two news classification datasets published by NLPCC2014 and Reuters, respectively. The proposed model achieves F-values by 88.5% and 51.8% on the two datasets. The experimental results show that our method outperforms all the traditional baseline systems.


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