Search results for "language processing"
showing 10 items of 421 documents
A system for sign language sentence recognition based on common sense context
2005
The paper proposes a complete framework for sign language recognition that integrates common sense in order to deal with sentences. The proposed system is based on a cognitive architecture allows modeling and managing the knowledge of the recognition process in a simple and robust way. The final abstraction level of this architecture introduces the semantic context and the analysis of the correctness of a sentence given a sequence of recognized signs. Experimentations are presented using the Italian sign language (LIS), and shows that the system maintains the recognition rate high when set of sign grows, correcting erroneous recognized single sign using the context
Linguistic interpretation of speech errors
2016
The paper is an attempt to illustrate the linguistic interpretation of speech, known that it remains insufficiently resolved, especially for Romanian. The cause is given by the multitude of criteria that can or should be considered important in speech processing. The aim of this study is to develope a computational tool in order to identify the possible errors related to the morphosintactic structure of speech. Our goal is to assist users who can receive automatically different suggestions that can help them to improve the quality of their text. Thus, we chose an interdisciplinary approach through speech analysis that brings together the key fields of linguistics, computer science and so on…
Target frames in British hotel websites
2015
This article centres on four-word phrase frames in British hospitality websites. Our aim is to identify those frames that are specific to this website genre, which we call target frames. Each phrase frame represents an identical sequence of words except for one variable word, that is A*BC or AB*D. The words that fill the slot, marked with an asterisk, are called fillers. We used a corpus-driven approach using KfNgram software to identify the phrase frames in our corpus (COMETVAL). We regard phrase frames as genre-specific when they are significantly more frequent than those found in the written section of the BNC, which represents General British English. We further filtered our selection o…
A New Approach to Investigate Students’ Behavior by Using Cluster Analysis as an Unsupervised Methodology in the Field of Education
2016
The problem of taking a set of data and separating it into subgroups where the ele- ments of each subgroup are more similar to each other than they are to elements not in the subgroup has been extensively studied through the statistical method of cluster analysis. In this paper we want to discuss the application of this method to the field of education: particularly, we want to present the use of cluster analysis to separate students into groups that can be recognized and characterized by common traits in their answers to a questionnaire, without any prior knowledge of what form those groups would take (unsupervised classification). We start from a detailed study of the data processing need…
The effects of associative and semantic priming in the lexical decision task.
2001
Four lexical decision experiments were conducted to examine under which conditions automatic semantic priming effects can be obtained. Experiments 1 and 2 analyzed associative/semantic effects at several very short stimulus-onset asynchronies (SOAs), whereas Experiments 3 and 4 used a single-presentation paradigm at two response-stimulus intervals (RSIs). Experiment 1 tested associatively related pairs from three semantic categories (synonyms, antonyms, and category coordinates). The results showed reliable associative priming effects at all SOAs. In addition, the correlation between associative strength and magnitude of priming was significant only at the shortest SOA (66 ms). When prime-t…
A sentence based system for measuring syntax complexity using a recurrent deep neural network
2018
In this paper we present a deep neural network model capable of inducing the rules that identify the syntax complexity of an Italian sentence. Our system, beyond the ability of choosing if a sentence needs of simplification, gives a score that represent the confidence of the model during the process of decision making which could be representative of the sentence complexity. Experiments have been carried out on one public corpus created specifically for the problem of text-simplification.
A recurrent deep neural network model to measure sentence complexity for the Italian Language
2019
Text simplification (TS) is a natural language processing task devoted to the modification of a text in such a way that the grammar and structure of the phrases is greatly simplified, preserving the underlying meaning and information contents. In this paper we give a contribution to the TS field presenting a deep neural network model able to detect the complexity of italian sentences. In particular, the system gives a score to an input text that identifies the confidence level during the decision making process and that could be interpreted as a measure of the sentence complexity. Experiments have been carried out on one public corpus of Italian texts created specifically for the task of TS…
Extracting Formal Models from Normative Texts
2016
Normative texts are documents based on the deontic notions of obligation, permission, and prohibition. Our goal is model such texts using the C-O Diagram formalism, making them amenable to formal analysis, in particular verifying that a text satisfies properties concerning causality of actions and timing constraints. We present an experimental, semi-automatic aid to bridge the gap between a normative text and its formal representation. Our approach uses dependency trees combined with our own rules and heuristics for extracting the relevant components. The resulting tabular data can then be converted into a C-O Diagram.