Search results for "natural language"
showing 10 items of 650 documents
Sign Languages Recognition Based on Neural Network Architecture
2017
In the last years, many steps forward have been made in speech and natural languages recognition and were developed many virtual assistants such as Apple’s Siri, Google Now and Microsoft Cortana. Unfortunately, not everyone can use voice to communicate to other people and digital devices. Our system is a first step for extending the possibility of using virtual assistants to speech impaired people by providing an artificial sign languages recognition based on neural network architecture.
Langage et Apprentissage en Interaction pour des Assistants Numériques Autonomes - Une Approche Développementale
2021
The rapid development of digital assistants (DA) opens the way to new modes of interaction. Some DA allows users to personalise the way they respond to queries, in particular by teaching them new procedures. This work proposes to use machine learning methods to enrich the linguistic and procedural generalisation capabilities of these systems. The challenge is to reconcile rapid learning skills, necessary for a smooth user experience, with a sufficiently large generalisation capacity. Though this is a natural human ability, it remains out-of-reach for artificial systems and this leads us to approach these issues from the perspective of developmental Artificial Intelligence. This work is thus…
Knowledge Acquisition in Conceptual Ontological Artificial Intelligence System
2009
The paper deals with active knowledge acquisition based on dialogue between AI system and its user. Presented method uses Conceptual Ontological Object Orientated System (COOS) to distinguish differences between concepts and to unequivocally process the input stream. In case of concepts, that do not exist in the system yet, adequate algorithms are being used to position them in ontological core. Separate concepts differ in attributes values or in sets of direct connections with other concepts. The communication aspect of the system deliver information that allow generating proper interpretation for userpsilas statement.
DeepEva: A deep neural network architecture for assessing sentence complexity in Italian and English languages
2021
Abstract Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (e.g., lexical, syntactical, morphological) to measure the grade of comprehensibility of a text. ATE can affect positively several different contexts such as Finance, Health, and Education. Moreover, it can support the research on Automatic Text Simplification (ATS), a research area that deals with the study of new methods for transforming a text by changing its lexicon and structure to meet specific reader needs. In this paper, we illustrate an ATE approach named De…
Using Tsetlin Machine to discover interpretable rules in natural language processing applications
2021
Tsetlin Machines (TM) use finite state machines for learning and propositional logic to represent patterns. The resulting pattern recognition approach captures information in the form of conjunctive clauses, thus facilitating human interpretation. In this work, we propose a TM-based approach to three common natural language processing (NLP) tasks, namely, sentiment analysis, semantic relation categorization and identifying entities in multi-turn dialogues. By performing frequent itemset mining on the TM-produced patterns, we show that we can obtain a global and a local interpretation of the learning, one that mimics existing rule-sets or lexicons. Further, we also establish that our TM base…
Combining a context aware neural network with a denoising autoencoder for measuring string similarities
2020
Abstract Measuring similarities between strings is central for many established and fast-growing research areas, including information retrieval, biology, and natural-language processing. The traditional approach to string similarity measurements is to define a metric with respect to a word space that quantifies and sums up the differences between characters in two strings; surprisingly, these metrics have not evolved a great deal over the past few decades. Indeed, the majority of them are still based on making a simple comparison between character and character distributions without considering the words context. This paper proposes a string metric that encompasses similarities between str…
A NEW COMPLEXITY FUNCTION FOR WORDS BASED ON PERIODICITY
2013
Motivated by the extension of the critical factorization theorem to infinite words, we study the (local) periodicity function, i.e. the function that, for any position in a word, gives the size of the shortest square centered in that position. We prove that this function characterizes any binary word up to exchange of letters. We then introduce a new complexity function for words (the periodicity complexity) that, for any position in the word, gives the average value of the periodicity function up to that position. The new complexity function is independent from the other commonly used complexity measures as, for instance, the factor complexity. Indeed, whereas any infinite word with bound…
On the Locality of Standard Search Operators in Grammatical Evolution
2014
Offspring should be similar to their parents and inherit their relevant properties. This general design principle of search operators in evolutionary algorithms is either known as locality or geometry of search operators, respectively. It takes a geometric perspective on search operators and suggests that the distance between an offspring and its parents should be less than or equal to the distance between both parents. This paper examines the locality of standard search operators used in grammatical evolution (GE) and genetic programming (GP) for binary tree problems. Both standard GE and GP search operators suffer from low locality since a substantial number of search steps result in an o…
Natural Language Parsing
2009
Automatic natural language processing captures a lion’s share of the attention in open information management. In one way or another, many applications have to deal with natural language input. In this chapter the authors investigate the problem of natural language parsing from the perspective of biolinguistics. They argue that the human mind succeeds in the parsing task without the help of languagespecific rules of parsing and language-specific rules of grammar. Instead, there is a universal parser incorporating a universal grammar. The main argument comes from language acquisition: Children cannot learn language specific parsing rules by rule induction due to the complexity of unconstrain…
Polarization Modulation Instability in All-Normal Dispersion Microstructured Optical Fibers with Quasi-Continuous 1064 nm Pump
2019
Polarization modulation instability (PMI) is a form of modulation instability that can exist in weakly birefringent optical fibers [1]. Sidebands can be generated by this effect when a polarization mode of the birefringent fiber is excited with an intense optical pump. The polarization state of the sidebands is orthogonal to the polarization of the pump signal. PMI has been observed in microstructured optical fibers (MOFs). PMI was reported in a large-air-filling fraction MOF that was pumped in the normal dispersion regime with visible light [2]. The coherent degradation of femtosecond supercontinuum light generated in all-normal dispersion (ANDi) MOFs due to PMI was recently investigated […