Additive particles, prosodic structure and focus sensitivity in Hungarian

The main aim of this article is to investigate the prosody-information structure interface in the analysis of the Hungarian additive particle is ‘also, too’. We present a prosodic study of narratives, collected through guided elicitation, and provide a prosodic basis for a focus-based analysis of is. Standard formal semantic approaches to the interpretation of additive particles regard additive particles as focus sensitive, hence the associate of the particle is focal and the focus interpretation (in terms of alternatives) is a significant part in its semantics. This view is considered crosslinguistically valid, although the discussion mostly concerns English. In Hungarian, the focus sensitivity of the additive particle is not directly transparent and needs more elaboration. In the relevant literature, the issue of focus marking with respect to the additive particle is has been insufficiently studied or merely stipulated. In this article, we argue for the importance of a more elaborate study of the prosody-information structure interface in the analysis of Hungarian additive particles. Accordingly, we provide data and its analysis to support our core argument and claims. Our study contributes to the overall understanding and analysis of is and to the general claims about focus marking and focus types in Hungarian. We aim to complement the standard semantic analyses by providing a prosodic analysis supporting the focus-sensitive analysis of is instead of merely stipulating an association with focus. On a more general level, we show that the various readings of additive particles can be explained by taking the prosodic patterns of the relevant constructions into account.

The grammatical representation of expletive negation

Expletive negation refers to constructions where a negator in the complement of certain lexical items does not change the polarity of the complement proposition. Jin & Koenig (2021) show that expletive negation occurs rather widely in languages of the world and in very similar environments. They propose a language production model of why such apparently illogical uses of negation arise in language after language. But their study does not address the grammatical status and representation of expletive negation. In this paper, we argue that expletive negation is part of the lexical knowledge speakers have of their language and that the negator in expletive negation constructions contributes a negation to a non-at-issue content associated with expletive negation triggers. We provide a Lexical Resource Semantics analysis of how triggers combine in a non-standard manner with the standard semantic content of their complements: the negation (and in some cases an additional modal operator) of the content of their complement is part of the trigger’s non-at-issue content while the scope of the negation is an argument of the trigger’s MAIN content. Finally, we suggest that the expletive use of the French negator ne includes a lexical constraint that requires it to modify a verb that reverse selects for an expletive negation trigger.

SEMANTIC ANALYSIS OF THE FIRST CITIES FROM A DECONSTRUCTION PERSPECTIVE

Abstrak_ Penelitian ini bertujuan untuk mengetahui identitas sebuah kota dari segi dekonstruksi. Karena dua fondasi penting dari dekonstruksi yaitu teks dan makna, serta hubungannya. The First Cities dipilih karena memiliki tingkat tanda teks dan upaya dilakukan untuk menganalisis maknanya berdasarkan isi metode analitik. Penelitian ini menggunakan analisis deduktif tiga langkah, termasuk persiapan, organisasi, laporan akhir atau kesimpulan. Pada tahap pertama, filsafat dekonstruksi berdasarkan pendapat diadvokasi. Kemudian, menentukan beberapa karakteristik semantik standar dari The First Cities. Terakhir, ditarik kesimpulan berdasarkan interpretasi semantik identitas The First Cities. Semua kota tertulis tampaknya cenderung membangkitkan makna tertentu, tetapi pada saat yang sama mempromosikan dan menekankan makna yang berlawanan dengan apa yang ingin mereka ungkapkan.Kata kunci: Dekonstruksi; Teks; Makna; Semantik Perkotaan; The First Cities. Abstract_ The purpose of this study is to investigate urban identity from a deconstruction perspective. Since two critical bases of Deconstruction are text and meaning and their relationships, so the first cities in a symbolic level were chosen as a text and have been tried to analyze their intentions based on the content analysis method. The study used deductive content analysis in three steps, including preparation, organization, and final report or conclusion. In the first step, it has accordingly been argued deconstruction philosophy based on Derrida's views; then determined some standard semantic features of the first cities. Finally, it has been shaped a conclusion based on a semantic interpretation of the first city's identity. It seems all cities as texts tend to provoke a special imaginary meaning but simultaneously, they promote and emphasize the opposite sense of what they want to show.Keywords: Deconstruction; Text; Meaning; Urban Semantics; The First Cities.

Query Expansion for Slovak to Bulgarian Language Machine Translation using Parallel Search

The paper presents results of the application of a statistical approach for Slovak to Bulgarian language machine translation. It uses Information Retrieval inspired search techniques and employs sever alalgorithmic steps of parallel statistical search with query expansion in Slovak-Bulgarian EUROPARL 7 Corpus using the Sketch Engine software and its scoring. The search includes the generation of concordances,collocations, word sketch differences, word sketches, and thesauri of the studied keyword (query) by using a statistical scoring, which is regarded as intermediate (inter-lingual) semantic standard presentation by means of which the studied keyword (from the source language) is mapped together with its possible translation equivalents (onto the target language. The results present the study of adjectival collocabillity in both Slovak and Bulgarian language from the corpus of political speech texts outlining the standard semantic relations based on the evaluation of statistical scoring. Finally, the advantages and shortcomings of the approach are discussed.

Segmentation-aware convolutional nets

This thesis introduces a method to both obtain segmentation information and integrate it uniformly within a convolutional neural network (CNN). This counter-acts the tendency of CNNs to produce smooth predictions, which is undesirable for pixel-wise prediction tasks, such as semantic segmentation. The segmentation information is obtained by a form of metric learning, where a CNN learns to compute pixel embeddings that reflect whether any pair of pixels is likely to belong to the same region. This information is then used within a larger network, to replace all convolutions with foreground-focused convolutions, where the foreground is determined adaptively at each image point by local embeddings. The resulting network is called a segmentation-aware CNN, because the network can change its behaviour at each image location according to local segmentation cues. The proposed method yields systematic improvements on a standard semantic segmentation benchmark when compared to a strong baseline.

Segmentation-aware convolutional nets

This thesis introduces a method to both obtain segmentation information and integrate it uniformly within a convolutional neural network (CNN). This counter-acts the tendency of CNNs to produce smooth predictions, which is undesirable for pixel-wise prediction tasks, such as semantic segmentation. The segmentation information is obtained by a form of metric learning, where a CNN learns to compute pixel embeddings that reflect whether any pair of pixels is likely to belong to the same region. This information is then used within a larger network, to replace all convolutions with foreground-focused convolutions, where the foreground is determined adaptively at each image point by local embeddings. The resulting network is called a segmentation-aware CNN, because the network can change its behaviour at each image location according to local segmentation cues. The proposed method yields systematic improvements on a standard semantic segmentation benchmark when compared to a strong baseline.

Applying Automatic Translation for Optical Music Recognition’s Encoding Step

Optical music recognition is a research field whose efforts have been mainly focused, due to the difficulties involved in its processes, on document and image recognition. However, there is a final step after the recognition phase that has not been properly addressed or discussed, and which is relevant to obtaining a standard digital score from the recognition process: the step of encoding data into a standard file format. In this paper, we address this task by proposing and evaluating the feasibility of using machine translation techniques, using statistical approaches and neural systems, to automatically convert the results of graphical encoding recognition into a standard semantic format, which can be exported as a digital score. We also discuss the implications, challenges and details to be taken into account when applying machine translation techniques to music languages, which are very different from natural human languages. This needs to be addressed prior to performing experiments and has not been reported in previous works. We also describe and detail experimental results, and conclude that applying machine translation techniques is a suitable solution for this task, as they have proven to obtain robust results.

Essentializing Inferences

Predicate nominals (e.g., ‘is a female’) seem to label or categorize their subjects, while their predicate adjective correlates (e.g, ‘is female’) merely attribute a property. Further, predicate nominals elicit essentializing inferential judgments about inductive potential as well as stable explanatory membership. Semantic data and research from developmental and cognitive psychology support that this distinction is robust and productive. I argue that while the difference between predicate nominals and predicate adjectives is elided by standard semantic theories, it ought not be. I then develop and defend a psychologically motivated semantic account that takes predicate nominals to involve attributing kind membership and to trigger a presupposition that underpins our essentialist judgments.

Exploring the city as text and dominant discourse place

The study has tried to answer the question of how the dominant discourse in the city tries to create meanings and forms an interpretation by using signs and symbols. Accordingly, common semiotics of Dur Untash city has been investigated. In three steps, including preparation, organization, and final report or conclusion, a content analysis method has been done. First, deconstruction views of reading place are explained and how an interpretation discourse is formed. Then we investigated some standard semantic features of Dur Untash city and an image of some familiar ideas and signs is projected. Finally, a bipolar semantic interpretation of these signs and images is presented. The dominant discourse of the city has wanted to catch a meaning, but none of its symbols and characters has such a valid capacity and authority. Therefore, the dominant discourses could not conjure spatial features controlled by meaning-making

Representing scales: Degree result clauses and emphaticnegative polarity items in Romanian

The paper proposes a representational re-encoding of the scalar, pragmatic accounts of NPI licensing within the framework of Lexical Resource Semantics (LRS). The analysis focuses on a less researched distribution pattern: emphatic NPIs occurring in result clause constructions that receive an intensification reading. We will provide a scalar extension of a standard semantic account of result clauses to capture the high degree interpretations. Our investigation will also offer new insights on NPI licensing in embedded clauses. We will primarily consider Romanian data.