Antonio Origlia


2022

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A Multi-source Graph Representation of the Movie Domain for Recommendation Dialogues Analysis
Antonio Origlia | Martina Di Bratto | Maria Di Maro | Sabrina Mennella
Proceedings of the Thirteenth Language Resources and Evaluation Conference

In dialogue analysis, characterising named entities in the domain of interest is relevant in order to understand how people are making use of them for argumentation purposes. The movie recommendation domain is a frequently considered case study for many applications and by linguistic studies and, since many different resources have been collected throughout the years to describe it, a single database combining all these data sources is a valuable asset for cross-disciplinary investigations. We propose an integrated graph-based structure of multiple resources, enriched with the results of the application of graph analytics approaches to provide an encompassing view of the domain and of the way people talk about it during the recommendation task. While we cannot distribute the final resource because of licensing issues, we share the code to assemble and process it once the reference data have been obtained from the original sources.

2017

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Graph Databases for Designing High-Performance Speech Recognition Grammars
Maria Di Maro | Marco Valentino | Anna Riccio | Antonio Origlia
Proceedings of the 12th International Conference on Computational Semantics (IWCS) — Short papers

2012

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W-PhAMT: A web tool for phonetic multilevel timeline visualization
Francesco Cutugno | Vincenza Anna Leano | Antonio Origlia
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper presents a web platform with an its own graphic environment to visualize and filter multilevel phonetic annotations. The tool accepts as input Annotation Graph XML and Praat TextGrids files and converts these files into a specific XML format. XML output is used to browse data by means of a web tool using a visualization metaphor, namely a timeline. A timeline is a graphical representation of a period of time, on which relevant events are marked. Events are usually distributed over many layers in a geometrical metaphor represented by segments and points spatially distributed with reference to a temporal axis. The tool shows all the annotations included in the uploaded dataset, allowing the listening of the entire file or of its parts. Filtering is allowed on annotation labels by means of string pattern matching. The web service includes cloud services to share data with other users. The tool is available at http://w-phamt.fisica.unina.it

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Prosomarker: a prosodic analysis tool based on optimal pitch stylization and automatic syllabi fication
Antonio Origlia | Iolanda Alfano
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Prosodic research in recent years has been supported by a number of automatic analysis tools aimed at simplifying the work that is requested to study intonation. The need to analyze large amounts of data and to inspect phenomena that are often ambiguous and difficult to model makes the prosodic research area an ideal application field for computer based processing. One of the main challenges in this field is to model the complex relations occurring between the segmental level, mainly in terms of syllable nuclei and boundaries, and the supra-segmental level, mainly in terms of tonal movements. The goal of our contribution is to provide a tool for automatic annotation of prosodic data, the Prosomarker, designed to give a visual representation of both segmental and suprasegmental events. The representation is intended to be as generic as possible to let researchers analyze specific phenomena without being limited by assumptions introduced by the annotation itself. A perceptual account of the pitch curve is provided along with an automatic segmentation of the speech signal into syllable-like segments and the tool can be used both for data exploration, in semi-automatic mode, and to process large sets of data, in automatic mode.