This study investigates the importance of human evaluations of coherence in predicting human judgments of holistic essay quality. Of secondary interest is the potential for computational indices of cohesion and coherence to model human judgments of coherence. The results indicate that human judgments of coherence are the most predictive features of holistic essay scores and that computational i...

Systematic acoustic variation reflects vocal tract dynamics; it provides the acoustic coherence that makes a signal sound like speech. It is thus basic to speech perception, defined as lexical access. Implications of this argument are that the perceptual system maps an informationallyrich signal directly onto lexical forms that are structurally rich, and that phonemes are not essential for lexi...

Recognizing coherent structure of a text is an essential task in natural language understanding. It is necessary, for example, to resolve anaphora, ellipsis, and ambiguity. One of the dominant factors of coherence of the text structure is lexical cohesion, namely the dependency relationship between words based on associative relations in common knowledge. This thesis proposes an objective and c...

EEG correlates of a range of psycholinguistic word properties were used to investigate the time course of access to psycholinguistic information during visual word recognition. Neurophysiological responses recorded in a visual lexical decision task were submitted to linear regression analysis. First, 10 psycholinguistic features of each of 300 stimulus words were submitted to a principal compon...

Automatic detection of lexical entailment, or hypernym detection, is an important NLP task. Recent hypernym detection measures have been based on the Distributional Inclusion Hypothesis (DIH). This paper assumes that the DIH sometimes fails, and investigates other ways of quantifying the relationship between the cooccurrence contexts of two terms. We consider the top features in a context vecto...

Discourse coherence is strongly associated with text quality, making it important to natural language generation and understanding. Yet existing models of coherence focus on measuring individual aspects of coherence (lexical overlap, rhetorical structure, entity centering) in narrow domains. In this paper, we describe domainindependent neural models of discourse coherence that are capable of me...

Discourse coherence is strongly associated with text quality, making it important to natural language generation and understanding. Yet existing models of coherence focus on measuring individual aspects of coherence (lexical overlap, rhetorical structure, entity centering) in narrow domains. In this paper, we describe domainindependent neural models of discourse coherence that are capable of me...

To alleviate the impact of Covid-19 pandemic on tourism, tourist facilities in Bali are informing visitors relevant health protocols, using posters to describe appropriate behaviours. Using critical discourse analysis, this study examines microstructure texts these identify their semantic, syntactic, lexical, and rhetorical elements. The findings show that semantic aspects consist background, i...

This paper investigates the influence of discourse features on text complexity assessment. To do so, we created two data sets based on the Penn Discourse Treebank and the Simple English Wikipedia corpora and compared the influence of coherence, cohesion, surface, lexical and syntactic features to assess text complexity. Results show that with both data sets coherence features are more correlate...