Guidelines for annotating the LUNA corpus with frame information

This document defines the annotation workflow aimed at adding frame information to the LUNA corpus of conversational speech. In particular, it details both the corpus pre-processing steps and the proper annotation process, giving hints about how to choose the frame and the frame element labels. Besides, the description of 20 new domain-specific and language-specific frames is reported. To our knowledge, this is the first attempt to adapt the frame paradigm to dialogs and at the same time to define new frames and frame elements for the specific domain of software/hardware assistance. The technical report is structured as follows: in Section 2 an overview of the FrameNet project is given, while Section 3 introduces the LUNA project and the annotation framework involving the Italian dialogs. Section 4 details the annotation workflow, including the format preparation of the dialog files and the annotation strategy. In Section 5 we discuss the main issues of the annotation of frame information in dialogs and we describe how the standard annotation procedure was changed in order to face such issues. Then, the 20 newly introduced frames are reported in Section 6

Active Learning for Dialogue Act Classification

Active learning techniques were employed for classification of dialogue acts over two dialogue corpora, the English human-human Switchboard corpus and the Spanish human-machine Dihana corpus. It is shown clearly that active learning improves on a baseline obtained through a passive learning approach to tagging the same data sets. An error reduction of 7% was obtained on Switchboard, while a factor 5 reduction in the amount of labeled data needed for classification was achieved on Dihana. The passive Support Vector Machine learner used as baseline in itself significantly improves the state of the art in dialogue act classification on both corpora. On Switchboard it gives a 31% error reduction compared to the previously best reported result

Analysis and automatic identification of spontaneous emotions in speech from human-human and human-machine communication

383 p.This research mainly focuses on improving our understanding of human-human and human-machineinteractions by analysing paricipants¿ emotional status. For this purpose, we have developed andenhanced Speech Emotion Recognition (SER) systems for both interactions in real-life scenarios,explicitly emphasising the Spanish language. In this framework, we have conducted an in-depth analysisof how humans express emotions using speech when communicating with other persons or machines inactual situations. Thus, we have analysed and studied the way in which emotional information isexpressed in a variety of true-to-life environments, which is a crucial aspect for the development of SERsystems. This study aimed to comprehensively understand the challenge we wanted to address:identifying emotional information on speech using machine learning technologies. Neural networks havebeen demonstrated to be adequate tools for identifying events in speech and language. Most of themaimed to make local comparisons between some specific aspects; thus, the experimental conditions weretailored to each particular analysis. The experiments across different articles (from P1 to P19) are hardlycomparable due to our continuous learning of dealing with the difficult task of identifying emotions inspeech. In order to make a fair comparison, additional unpublished results are presented in the Appendix.These experiments were carried out under identical and rigorous conditions. This general comparisonoffers an overview of the advantages and disadvantages of the different methodologies for the automaticrecognition of emotions in speech

Design of a Controlled Language for Critical Infrastructures Protection

We describe a project for the construction of controlled language for critical infrastructures protection (CIP). This project originates from the need to coordinate and categorize the communications on CIP at the European level. These communications can be physically represented by official documents, reports on incidents, informal communications and plain e-mail. We explore the application of traditional library science tools for the construction of controlled languages in order to achieve our goal. Our starting point is an analogous work done during the sixties in the field of nuclear science known as the Euratom Thesaurus.JRC.G.6-Security technology assessmen

Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020

On behalf of the Program Committee, a very warm welcome to the Seventh Italian Conference on Computational Linguistics (CLiC-it 2020). This edition of the conference is held in Bologna and organised by the University of Bologna. The CLiC-it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after six years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

Towards an authentic argumentation literacy test

A central goal of education is to improve argumentation literacy. How do we know how well this goal is achieved? Can we measure argumentation literacy? The present study is a preliminary step towards measuring the efficacy of education with regards to argumentation literacy. Tests currently in use to determine critical thinking skills are often similar to IQ-tests in that they predominantly measure logical and mathematical abilities. Thus, they may not measure the various other skills required in understanding authentic argumentation. To identify the elements of argumentation literacy, this exploratory study begins by surveying introductory textbooks within argumentation theory, critical thinking, and rhetoric. Eight main abilities have been identified. Then, the study outlines an Argumentation Literacy Test that would comprise these abilities suggested by the literature. Finally, the study presents results from a pilot of a version of such a test and discusses needs for further development

A Strategy for Multilingual Spoken Language Understanding Based on Graphs of Linguistic Units

[EN] In this thesis, the problem of multilingual spoken language understanding is addressed using graphs to model and combine the different knowledge sources that take part in the understanding process. As a result of this work, a full multilingual spoken language understanding system has been developed, in which statistical models and graphs of linguistic units are used. One key feature of this system is its ability to combine and process multiple inputs provided by one or more sources such as speech recognizers or machine translators. A graph-based monolingual spoken language understanding system was developed as a starting point. The input to this system is a set of sentences that is provided by one or more speech recognition systems. First, these sentences are combined by means of a grammatical inference algorithm in order to build a graph of words. Next, the graph of words is processed to construct a graph of concepts by using a dynamic programming algorithm that identifies the lexical structures that represent the different concepts of the task. Finally, the graph of concepts is used to build the best sequence of concepts. The multilingual case happens when the user speaks a language different to the one natively supported by the system. In this thesis, a test-on-source approach was followed. This means that the input sentences are translated into the system's language, and then they are processed by the monolingual system. For this purpose, two speech translation systems were developed. The output of these speech translation systems are graphs of words that are then processed by the monolingual graph-based spoken language understanding system. Both in the monolingual case and in the multilingual case, the experimental results show that a combination of several inputs allows to improve the results obtained with a single input. In fact, this approach outperforms the current state of the art in many cases when several inputs are combined.[ES] En esta tesis se aborda el problema de la comprensión multilingüe del habla utilizando grafos para modelizar y combinar las diversas fuentes de conocimiento que intervienen en el proceso. Como resultado se ha desarrollado un sistema completo de comprensión multilingüe que utiliza modelos estadísticos y grafos de unidades lingüísticas. El punto fuerte de este sistema es su capacidad para combinar y procesar múltiples entradas proporcionadas por una o varias fuentes, como reconocedores de habla o traductores automáticos. Como punto de partida se desarrolló un sistema de comprensión multilingüe basado en grafos. La entrada a este sistema es un conjunto de frases obtenido a partir de uno o varios reconocedores de habla. En primer lugar, se aplica un algoritmo de inferencia gramatical que combina estas frases y obtiene un grafo de palabras. A continuación, se analiza el grafo de palabras mediante un algoritmo de programación dinámica que identifica las estructuras léxicas correspondientes a los distintos conceptos de la tarea, de forma que se construye un grafo de conceptos. Finalmente, se procesa el grafo de conceptos para encontrar la mejo secuencia de conceptos. El caso multilingüe ocurre cuando el usuario habla una lengua distinta a la original del sistema. En este trabajo se ha utilizado una estrategia test-on-source, en la cual las frases de entrada se traducen al lenguaje del sistema y éste las trata de forma monolingüe. Para ello se han propuesto dos sistemas de traducción del habla cuya salida son grafos de palabras, los cuales son procesados por el algoritmo de comprensión basado en grafos. Tanto en la configuración monolingüe como en la multilingüe los resultados muestran que la combinación de varias entradas permite mejorar los resultados obtenidos con una sola entrada. De hecho, esta aproximación consigue en muchos casos mejores resultados que el actual estado del arte cuando se utiliza una combinación de varias entradas.[CA] Aquesta tesi tracta el problema de la comprensió multilingüe de la parla utilitzant grafs per a modelitzar i combinar les diverses fonts de coneixement que intervenen en el procés. Com a resultat s'ha desenvolupat un sistema complet de comprensió multilingüe de la parla que utilitza models estadístics i grafs d'unitats lingüístiques. El punt fort d'aquest sistema és la seua capacitat per combinar i processar múltiples entrades proporcionades per una o diverses fonts, com reconeixedors de la parla o traductors automàtics. Com a punt de partida, es va desenvolupar un sistema de comprensió monolingüe basat en grafs. L'entrada d'aquest sistema és un conjunt de frases obtingut a partir d'un o més reconeixedors de la parla. En primer lloc, s'aplica un algorisme d'inferència gramatical que combina aquestes frases i obté un graf de paraules. A continuació, s'analitza el graf de paraules mitjançant un algorisme de programació dinàmica que identifica les estructures lèxiques corresponents als distints conceptes de la tasca, de forma que es construeix un graf de conceptes. Finalment, es processa aquest graf de conceptes per trobar la millor seqüència de conceptes. El cas multilingüe ocorre quan l'usuari parla una llengua diferent a l'original del sistema. En aquest treball s'ha utilitzat una estratègia test-on-source, en la qual les frases d'entrada es tradueixen a la llengua del sistema, i aquest les tracta de forma monolingüe. Per a fer-ho es proposen dos sistemes de traducció de la parla l'eixida dels quals són grafs de paraules. Aquests grafs són posteriorment processats per l'algorisme de comprensió basat en grafs. Tant per la configuració monolingüe com per la multilingüe els resultats mostren que la combinació de diverses entrades és capaç de millorar el resultats obtinguts utilitzant una sola entrada. De fet, aquesta aproximació aconsegueix en molts casos millors resultats que l'actual estat de l'art quan s'utilitza una combinació de diverses entrades.Calvo Lance, M. (2016). A Strategy for Multilingual Spoken Language Understanding Based on Graphs of Linguistic Units [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/62407TESI

Proceedings of the Eighth Italian Conference on Computational Linguistics CliC-it 2021

The eighth edition of the Italian Conference on Computational Linguistics (CLiC-it 2021) was held at Università degli Studi di Milano-Bicocca from 26th to 28th January 2022. After the edition of 2020, which was held in fully virtual mode due to the health emergency related to Covid-19, CLiC-it 2021 represented the first moment for the Italian research community of Computational Linguistics to meet in person after more than one year of full/partial lockdown