The aim of this critical review paper is threefold: (a) to provide an insight on the impact of ontology engineering methodologies (OEMs) to the evolution of living and reused ontologies, (b) to update the ontology engineering (OE) community on the status and trends in OEMs and of their use in practice and (c) to propose a set of recommendations for working ontologists to consider during the life cycle of living, evolved and reused ontologies. The work outlined in this critical review paper has been motivated by the need to address critical issues on keeping ontologies alive and evolving while these are shared in wide communities. It is argued that the engineering of ontologies must follow a well-defined methodology, addressing practical aspects that would allow (sometimes wide) communities of experts and ontologists to reach consensus on developments and keep the evolution of ontologies ‘in track’. In doing so, specific collaborative and iterative tool-supported tasks and phases within a complete and evaluated ontology life cycle are necessary. This way the engineered ontologies can be considered ‘shared, commonly agreed and continuously evolved “live” conceptualizations’ of domains of discourse. Today, in the era of Linked Data and Knowledge Graphs, it is more necessary than ever not to neglect to consider the recommendations that OEMs explicitly and implicitly introduce and their implications to the evolution of living ontologies. This paper reports on the status of OEMs, identifies trends and provides recommendations based on the findings of an analysis that concerns the impact of OEMs to the status of well-known, widely used and representative ontologies.

Today, a considerable proportion of the public political discourse on nationwide elections proceeds in Online Social Networks. Through analyzing this content, we can discover the major themes that prevailed during the discussion, investigate the temporal variation of positive and negative sentiment and examine the semantic proximity of these themes. According to existing studies, the results of similar tasks are heavily dependent on the quality and completeness of dictionaries for linguistic preprocessing, entity discovery and sentiment analysis. Additionally, noise reduction is achieved with methods for sarcasm detection and correction. Here we report on the application of these methods on the complete corpus of tweets regarding two local electoral events of worldwide impact: the Greek referendum of 2015 and the subsequent legislative elections. To this end, we compiled novel dictionaries for sentiment and entity detection for the Greek language tailored to these events. We subsequently performed volume analysis, sentiment analysis, sarcasm correction and topic modeling. Results showed that there was a strong anti-austerity sentiment accompanied with a critical view on European and Greek political actions.

No abstract

No abstract

Text documents usually embody visually oriented meta-information in the form of complex visual structures, such as tables. The semantics involved in such objects result in poor and ambiguous text-to-speech synthesis. Although most speech synthesis frameworks allow the consistent control of an abundance of parameters, such as prosodic cues, through appropriate markup, there is no actual prosodic specification to speech-enable visual elements. This paper presents a method for the acoustic specification modelling of simple and complex data tables, derived from the human paradigm. A series of psychoacoustic experiments were set up for providing speech properties obtained from prosodic analysis of natural spoken descriptions of data tables. Thirty blind and 30 sighted listeners selected the most prominent natural rendition. The derived prosodic phrase accent and pause break placement vectors were modelled using the ToBI semiotic system to successfully convey semantically important visual information through prosody control. The quality of the information provision of speech-synthesized tables when utilizing the proposed prosody specification was evaluated by first-time listeners. The results show a significant increase (from 14 to 20% depending on the table type) of the user subjective understanding (overall impression, listening effort and acceptance) of the table data semantic structure compared to the traditional linearized speech synthesis of tables. Furthermore, it is proven that successful prosody manipulation can be applied to data tables using generic specification sets for certain table types and browsing techniques, resulting in improved data comprehension.

Abstract. A significant challenge in Text-to-Speech (TtS) synthesis is the formulation of the prosodic structures (phrase breaks, pitch accents, phrase accents and boundary tones) of utterances. The prediction of these elements robustly relies on the accuracy and the quality of error-prone linguistic procedures, such as the identification of the part-of-speech and the syntactic tree. Additional linguistic factors, such as rhetorical relations, improve the naturalness of the prosody, but are hard to extract from plain texts. In this work, we are proposing a method to generate enhanced prosodic events for TtS by utilizing accurate, error-free and high-level linguistic information. We are also presenting an appropriate XML annotation scheme to encode syntax, grammar, new or given information, phrase subject/object information, as well as rhetorical elements. These linguistically enriched has have been utilized to build realistic machine learning models for the prediction of the prosodic structures in terms of segmental information and ToBI marks. The methodology has been applied by exploiting a Natural Language Generator (NLG) system. The trained models have been built using classification via regression trees and the results strongly indicate the realistic effect on the generated prosody. The evaluation of this approach has been made by comparing the models produced by the enriched documents to those produced by plain text of the same domain. The results show an improved accuracy of up to 23%.

Abstract. Transferring a structure from the visual modality to the aural one presents a difficult challenge. In this work we are experimenting with prosody modeling for the synthesized speech representation of tabulated structures. This is achieved by analyzing naturally spoken descriptions of data tables and a following feedback by blind and sighted users. The derived prosodic phrase accent and pause break placement and values are examined in terms of successfully conveying semantically important visual information through prosody control in Table-to-Speech synthesis. Finally, the quality of the information provision of synthesized tables when utilizing the proposed prosody specification is studied against plain synthesis.

No abstract