Identifying which words present in a text may be difficult to understand by common readers is well-known subtask complexity analysis. The advent of deep language models has also established the new state-of-the-art this task means end-to-end semi-supervised (pre-trained) and downstream training of, mainly, transformer-based neural networks. Nevertheless, usefulness traditional linguistic featur...

We describe a metric for estimating the quality of Statistical Machine Translation (SMT) output based on syntactic features extracted using Combinatory Categorial Grammar (CCG). CCG has been demonstrated to be better suited to deal with SMT texts than context free phrase structure grammar formalisms. We use CCG features to estimate the grammaticality of the translations by dividing them into ma...

This paper proposes a method to recognize anger-dialog based on linguistic and para-linguistic information in speech. Anger is classified into two types; HotAnger (agitated) and ColdAnger (calm). Conventional prosody-features based on para-linguistic can reliably recognize the former but not the latter. To recognize anger more robustly, we apply other para-linguistic cues named dialog-features ...

The linguistic features analysis for input text plays an important role in achieving natural prosodic control in text-to-speech (TTS) systems. In a conventional scheme, experts refine suspicious if-then rules and change the tree structure manually to obtain correct analysis results when input texts that have been analyzed incorrectly. However, altering the tree structure drastically is difficul...

Fossilization has become the focus of many L2 studies since its introduction in 1972 as many learners fail to achieve native-speaker competence. Researchers have tried to unravel the causes of fossilization, among which noticing has been claimed to be of great importance. This  study  aimed  to  explore  the  effect  of  noticing  on  fossilization.  To  achieve  this  aim,  a mixed-methods app...

Debate and deliberation play essential roles in politics and government, but most models presume that debates are won mainly via superior style or agenda control. Ideally, however, debates would be won on the merits, as a function of which side has the stronger arguments. We propose a predictive model of debate that estimates the effects of linguistic features and the latent persuasive strength...

In teaching and learning of English as a foreign language, the Internet serves as a source of authentic listening material, enabling learners to practice English in real contexts. An adaptive computer-assisted language learning and teaching system can pick up news clips as authentic materials from the Internet according to learner listening proficiency if it is equipped with a listenability mea...

A common strategy for Question Answering systems uses high quality ontologies or databases in order to efficiently answer questions. Some approaches to build or enrich these databases rely on machine learning classifiers for obtaining semantically related terms from unstructured text. These classifiers are based on features that may contain several kinds of linguistic knowledge: from orthograph...

This paper describes a robust linear classification system for Named Entity Recognition. A similar system has been applied to the CoNLL text chunking shared task with state of the art performance. By using different linguistic features, we can easily adapt this system to other token-based linguistic tagging problems. The main focus of the current paper is to investigate the impact of various lo...

Our approach enables: • accurate prediction of target translation stem and suffix given fixed amount of context • automatic learning of relevant features with neural network architecture Choosing the correct surface form requires linguistic features of source and target context: • in phrase-based SMT, access to source context depends on phrase segmentation • linguistic features depend on availa...