Search results for "Sentence"
showing 10 items of 257 documents
Towards Open Domain Chatbots—A GRU Architecture for Data Driven Conversations
2018
Understanding of textual content, such as topic and intent recognition, is a critical part of chatbots, allowing the chatbot to provide relevant responses. Although successful in several narrow domains, the potential diversity of content in broader and more open domains renders traditional pattern recognition techniques inaccurate. In this paper, we propose a novel deep learning architecture for content recognition that consists of multiple levels of gated recurrent units (GRUs). The architecture is designed to capture complex sentence structure at multiple levels of abstraction, seeking content recognition for very wide domains, through a distributed scalable representation of content. To …
Body Gestures and Spoken Sentences: A Novel Approach for Revealing User’s Emotions
2017
In the last decade, there has been a growing interest in emotion analysis research, which has been applied in several areas of computer science. Many authors have con- tributed to the development of emotion recognition algorithms, considering textual or non verbal data as input, such as facial expressions, gestures or, in the case of multi-modal emotion recognition, a combination of them. In this paper, we describe a method to detect emotions from gestures using the skeletal data obtained from Kinect-like devices as input, as well as a textual description of their meaning. The experimental results show that the correlation existing between body movements and spoken user sentence(s) can be u…
Attention-based Model for Evaluating the Complexity of Sentences in English Language
2020
The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…
Deep neural attention-based model for the evaluation of italian sentences complexity
2020
In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.
What is an indirect speech act?
2019
Abstract The notion of an indirect speech act is at the very heart of cognitive pragmatics, yet, after nearly 50 years of orthodox (Searlean) speech act theory, it remains largely unclear how this notion can be explicated in a proper way. In recent years, two debates about indirect speech acts have stood out. First, a debate about the Searlean idea that indirect speech acts constitute a simultaneous realization of a secondary and a primary act. Second, a debate about the reasons for the use of indirect speech acts, in particular about whether this reason is to be seen in strategic advantages and/or observation of politeness demands. In these debates, the original pragmatic conception of sen…
Signs activate their written word translation in deaf adults: An ERP study on cross-modal co-activation in German Sign Language
2020
Since signs and words are perceived and produced in distinct sensory-motor systems, they do not share a phonological basis. Nevertheless, many deaf bilinguals master a spoken language with input merely based on visual cues like mouth representations of spoken words and orthographic representations of written words. Recent findings further suggest that processing of words involves cross-language cross-modal co-activation of signs in deaf and hearing bilinguals. Extending these findings in the present ERP-study, we recorded the electroencephalogram (EEG) of fifteen congenitally deaf bilinguals of German Sign Language (DGS) (native L1) and German (early L2) as they saw videos of semantically a…
Play it by ear? An ERP study of Chinese polysemous verb yǒu
2021
Abstract Mandarin Chinese yŏu is a polysemous verb. It can be interpreted as meaning either ‘have’ or ‘there be/exist’ in sentences of the form ‘NP1 yŏu NP2’, which can correspondingly be analyzed as either a Have-Possessive construction (‘NP1 has NP2’) or an existential/locative construction (‘(At/in) NP1 there is NP2’), or both. This study used event-related brain potentials to investigate whether and how the interpretation of yŏu in a given ‘NP1 yŏu NP2’ construction is determined by the semantics of the nouns involved and their relationship. Twenty-seven participants read sentences of this construction. The results showed that there were different patterns of brain activity that can be …
Comparing the Quality of Neural Machine Translation and Professional Post-Editing
2019
This empirical corpus study explores the quality of neural machine translations (NMT) and their post-edits (NMTPE) at the German Department of the European Commission’s Directorate-General for Translation (DGT) by evaluating NMT outputs, NMTPE, and respective revisions (REV) with the automatic error annotation tool Hjerson (Popovic 2011) and the more fine-grained manual MQM framework (Lommel 2014). Results show that quality assurance measures by post-editors and revisors at the DGT are most often necessary for lexical errors. More specifically, if post-editors correct mistranslations, terminology or stylistic errors in an NMT sentence, revisors are likely to correct the same type of error i…
Different Languages - Different Sentence Types? On Exclamative Sentences
2016
It is not equally easy for all languages to establish an exclamative sentence type. It seems the easiest for those languages that feature a morphological marking for an exclamative sentence type like Turkish or Vietnamese. English on the other hand is a language that does not mark exclamative clauses with an easily identifiable marker but uses certain preferred constructions, which allow us to separate a class of ‘exclamative sentences’ from other sentence types. However, there is another class of languages for which it is even harder to determine if ‘exclamative sentences’ exist as a sentence type. In those languages, these sentences share a striking amount of formal properties with senten…
Combining Machine Translated Sentence Chunks from Multiple MT Systems
2018
This paper presents a hybrid machine translation (HMT) system that pursues syntactic analysis to acquire phrases of source sentences, translates the phrases using multiple online machine translation (MT) system application program interfaces (APIs) and generates output by combining translated chunks to obtain the best possible translation. The aim of this study is to improve translation quality of English – Latvian texts over each of the individual MT APIs. The selection of the best translation hypothesis is done by calculating the perplexity for each hypothesis using an n-gram language model. The result is a phrase-based multi-system machine translation system that allows to improve MT out…