Automatisation of intonation modelling and its linguistic anchoring

This paper presents a fully machine-driven approach for intonation description and its linguistic interpretation. For this purpose,a new intonation model for bottom-up F0 contour analysis and synthesis is introduced, the CoPaSul model which is designed in the tradition of parametric, contour-based, and superpositional approaches. Intonation is represented by a superposition of global and local contour classes that are derived from F0 parameterisation. These classes were linguistically anchored with respect to information status by aligning them with a text which had been coarsely analysed for this purpose by means of NLP techniques. To test the adequacy of this data-driven interpretation a perception experiment was carried out, which confirmed 80% of the findings

Natural language processing

Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information extraction, information retrieval, etc., including domain-specific applications; (ii) natural language interfaces; (iii) NLP in the context of www and digital libraries ; and (iv) evaluation of NLP systems

Discourse relations and conjoined VPs: automated sense recognition

Sense classification of discourse relations is a sub-task of shallow discourse parsing. Discourse relations can occur both across sentences (inter-sentential) and within sentences (intra-sentential), and more than one discourse relation can hold between the same units. Using a newly available corpus of discourse-annotated intra-sentential conjoined verb phrases, we demonstrate a sequential classification system for their multi-label sense classification. We assess the importance of each feature used in the classification, the feature scope, and what is lost in moving from gold standard manual parses to the output of an off-the-shelf parser

Better Document-level Sentiment Analysis from RST Discourse Parsing

Discourse structure is the hidden link between surface features and document-level properties, such as sentiment polarity. We show that the discourse analyses produced by Rhetorical Structure Theory (RST) parsers can improve document-level sentiment analysis, via composition of local information up the discourse tree. First, we show that reweighting discourse units according to their position in a dependency representation of the rhetorical structure can yield substantial improvements on lexicon-based sentiment analysis. Next, we present a recursive neural network over the RST structure, which offers significant improvements over classification-based methods.Comment: Published at Empirical Methods in Natural Language Processing (EMNLP 2015

Towards Multi-Modal Interactions in Virtual Environments: A Case Study

We present research on visualization and interaction in a realistic model of an existing theatre. This existing ‘Muziek¬centrum’ offers its visitors information about performances by means of a yearly brochure. In addition, it is possible to get information at an information desk in the theatre (during office hours), to get information by phone (by talking to a human or by using IVR). The database of the theater holds the information that is available at the beginning of the ‘theatre season’. Our aim is to make this information more accessible by using multi-modal accessible multi-media web pages. A more general aim is to do research in the area of web-based services, in particu¬lar interactions in virtual environments

Speech synthesis, Speech simulation and speech science

Speech synthesis research has been transformed in recent years through the exploitation of speech corpora - both for statistical modelling and as a source of signals for concatenative synthesis. This revolution in methodology and the new techniques it brings calls into question the received wisdom that better computer voice output will come from a better understanding of how humans produce speech. This paper discusses the relationship between this new technology of simulated speech and the traditional aims of speech science. The paper suggests that the goal of speech simulation frees engineers from inadequate linguistic and physiological descriptions of speech. But at the same time, it leaves speech scientists free to return to their proper goal of building a computational model of human speech production

Political Discourse Analysis through Solving Problems of Graph Theory

In this article, we show how, using graph theory, we can make a content analysis of political discourse. Assumptions of this analysis are: • we have a corpus of speech of each party or candidate; • we consider that speech conveys economic, political, socio-cultural values, these taking the form of words or word families; • we consider that there are interdependences between the values of a political discourse; they are given by the co-occurrence of two values, as words in the text, within a well defined fragment, or they are determined by the internal logic of political discourse; • established links between values in a political speech have associated positive numbers indicating the "power" of those links; these "powers" are defined according to both the number of co-occurrences of values, and the internal logic of the discourse where they occur. In this context we intend to highlight the following: a) which is the dominant value in a political speech; b) which groups of values have ties between them and have no connection with the rest; c) which is the order in which political values should be set in order to obtain an equivalent but more synthetic speech compared to the already given one; d) which are the links between values that form the "core" political speech. To solve these problems, we shall use the Political Analyst program. After that, we shall present the concepts necessary to the understanding of the introductory graph theory, useful in understanding the analysis of the software and then the operation of the program. This paper extends the previous paper [6]graph theory, discourse analysis, political programs