Neural network based approaches for sentence relation modeling automatically generate hidden matching features from raw sentence pairs. However, the quality of matching feature representation may not be satisfied due to complex semantic relations such as entailment or contradiction. To address this challenge, we propose a new deep neural network architecture that jointly leverage pre-trained wo...

This paper describes the use of a low-dimensional vector representation of sentence acoustics to control the output of a feed-forward deep neural network text-to-speech system on a sentence-by-sentence basis. Vector representations for sentences in the training corpus are learned during network training along with other parameters of the model. Although the network is trained on a frame-by-fram...

Sentence level evaluation in MT has turned out far more difficult than corpus level evaluation. Existing sentence level metrics employ a limited set of features, most of which are rather sparse at the sentence level, and their intricate models are rarely trained for ranking. This paper presents a simple linear model exploiting 33 relatively dense features, some of which are novel while others a...

Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease, making choices with re...

....................................................................................................................................... i Significance to defence and security ................................................................................................ i Résumé .......................................................................................................................

The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Summarisation. In this paper, we treat event detection as a sentence level text classification problem. We compare the performance of two approaches to this task: a Support Vector Machine (SVM) classifier and a Language Modeling (LM) ap...

Reading is considered an inefficient activity that requires independent detection of individual letters without integrating word or sentence information. We studied the use of word- and sentence-shape information using word discrimination and reading tasks with spatially distorted text in 18 naïve observers. Threshold durations were measured as a function of the wavelength and magnitude of spat...

We present an implementation of a discourse parsing system for a lexicalized Tree-Ajoining Grammar for discourse, specifying the integration of sentence and discourse level processing. Our system is based on the assumption that the compositional aspects of semantics at the discourse-level parallel those at the sentence-level. This coupling is achieved by factoring away inferential semantics and...

the study of the sentence and its divisions has been always a cause of difference in syntactical viewpoints among the ancient and modern arab grammarians. ibn hesham sees three divisions for the arabic sentence: the noun sentence, the verb sentence and the adverb sentence. the adverb sentence in his view is that in which a time or place adverb or a prepositional phrase is the predicate proceede...

Hybrid System Combination for Machine Translation: An Integration of Phrase-level and Sentence-level Combination Approaches Wei-Yun Ma Given the wide range of successful statistical MT approaches that have emerged recently, it would be beneficial to take advantage of their individual strengths and avoid their individual weaknesses. Multi-Engine Machine Translation (MEMT) attempts to do so by ei...