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Abstract

In the scope of this research, we aim to give an overview of the currently existing solutions for machine translation and we assess their performance on the English-Hungarian language pair. Hungarian is considered to be a challenging language for machine translation because it has a highly different grammatical structure and word ordering compared to English. We probed various machine translation systems from both academic and industrial applications. One key highlight of our work is that our models (Marian NMT, BART) performed significantly better than the solutions offered by most of the market-leader multinational companies. Finally, we fine-tuned different pre-finetuned models (mT5, mBART, M2M100) for English-Hungarian translation, which achieved state-of-the-art results in our test corpora.

Open access

Abstract

Ancient classical culture usually links gambling (plays with knucklebones, dice, pawns) with divination and love's matters. It is noteworthy, to examine playing by knucklebones (Greek astragaloi). The connection between astragals, games and the erotic sphere clearly appears in Eros-Ganymede episode in the 3rd Book of Apollonius' Argonautica. A fragment of Callimachus also deals with knucklebones. Many Greek lyric and epigrammatic poets echo this topic. In sum, Apollonius allows us to discover a usual imagery: Eros as a player with knucklebones shows that Love masters the human life. It is thus an evident symbol of fate.

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Abstract

One of the most important NLP tasks for the industry today is to produce an extract from longer text documents. This task is one of the hottest topics for the researchers and they have created some solutions for English. There are two types of the text summarization called extractive and abstractive. The goal of the first task is to find the relevant sentences from the text, while the second one should generate the extraction based on the original text. In this research I have built the first solutions for Hungarian text summarization systems both for extractive and abstractive subtasks. Different kinds of neural transformer-based methods were used and evaluated. I present in this publication the first Hungarian abstractive summarization tool based on mBART and mT5 models, which gained state-of-the-art results.

Open access

Abstract

In a lesser known mythological tradition Eros is the son of Iris and Zephyros. His mother, Iris, belongs to a lineage of winged beings who are connected to a pre-cosmic dimension that precedes the historical reality ruled and guaranteed by Zeus. His father, Zephyros, is a wind and also a winged being whose story is linked to the birth of other superhuman beings who contribute to the foundation of a reality not yet fully established. Equally, Eros is a primordial superhuman being, whose nature at a mythical level is that of preceding the foundation of the cosmos. The purpose of this work is to investigate – through the meanders of mythological heritage – which elements of the narratives referring to these characters are relevant to classical Greek culture.

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Ildikó Enyedi: Testről és lélekről

Skizze zu einer semiotischen Analyse eines Films zwischen Romantik, Strukturalismus und Psychoanalyse

Hungarian Studies
Author:
Wolfgang Müller-Funk

Abstract

This article is about Ildiko Enyedi's film “Testről és lélekről”. It proposes a semiotic analyse. Its thematic frame is a theory of the fantastic literature and film and refers to Tzvetan Todorov (part 1). Following Roand Barthes “S/Z” it discusses the codes in the film, the sequences and spaces in the film (part 2). In the next part the composition of the film comes into play (e. g. repetition, analogy). The fourth part is dedicated to the uncanny and fantastic element that are created by a lack of knowledge about the world in the and the figures of the movy. The article refers to Freud's “Traumdeutung”. Part 5 analyses the funktion of silence in the film on several levels (level of narrating, communication of the figures in the film). The film is seen in a post-romantic tradition which is in-written in “classical modernism”.

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Abstract

In this paper, we argue that the very convincing performance of recent deep-neural-model-based NLP applications has demonstrated that the distributionalist approach to language description has proven to be more successful than the earlier subtle rule-based models created by the generative school. The now ubiquitous neural models can naturally handle ambiguity and achieve human-like linguistic performance with most of their training consisting only of noisy raw linguistic data without any multimodal grounding or external supervision refuting Chomsky's argument that some generic neural architecture cannot arrive at the linguistic performance exhibited by humans given the limited input available to children. In addition, we demonstrate in experiments with Hungarian as the target language that the shared internal representations in multilingually trained versions of these models make them able to transfer specific linguistic skills, including structured annotation skills, from one language to another remarkably efficiently.

Open access
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Abstract

Although the name of Ferenc Hunyadi is known in Hungarian literary history mainly for his Hungarian-language historical song about the peril of Troy, there also exist more than five thousand lines of Latin poetry by him which have not been collected or published since the 16th century. Another eleven of his poems are known from a manuscript written by a Unitarian pastor in the early 17th century. A further, one-distich poem was recorded by István Szamosközy. The date of composition of his poems in manuscript can be placed roughly between the end of 1586 and 1599. In addition to these, there is also a manuscript kept in Oxford in which Hunyadi gives prescriptions for febrile diseases. As a starting point for further research, this paper summarises what is currently known about Hunyadi and his works.

Open access

Abstract

Hungarian has a prolific system of complex predicate formation combining a separable preverb and a verb. These combinations can enter a wide range of constructions, with the preverb preserving its separability to some extent, depending on the construction in question. The primary concern of this paper is to advance the investigation of these phenomena by presenting PrevDistro (Preverb Distributions), an open-access dataset containing more than 41.5 million corpus occurrences of 49 preverb construction types. The paper gives a detailed introduction to PrevDistro, including design considerations, methodology and the resulting dataset's main characteristics.

Open access

Abstract

Nowadays, it is quite common in linguistics to base research on data instead of introspection. There are countless corpora – both raw and linguistically annotated – available to us which provide essential data needed. Corpora are large in most cases, ranging from several million words to some billion words in size, clearly not suitable to investigate word by word by close reading. Basically, there are two ways to retrieve data from them: (1) through a query interface or (2) directly by automatic text processing. Here we present principles on how to soundly and effectively collect linguistic data from corpora by querying i.e. without knowledge of programming to directly manipulate the data. What is worth thinking about, which tools to use, what to do by default and how to solve problematic cases. In sum, how to obtain correct and complete data from corpora to do linguistic research.

Open access