In this research we aim to detect subjective sentences in spontaneous speech and label them for polarity. We introduce a novel technique wherein subjective patterns are learned from both labeled and unlabeled data, using n-grams with varying levels of lexical instantiation. Applying this technique to meeting speech, we gain significant improvement over state-of-theart approaches and demonstrate...

This paper studies the problem of using weighted Ngrams of chord sequences to construct the profile of a composer. The N-gram profile of a chord sequence is the collection of all N-grams appearing in a sequence where each N-gram is given a weight proportional to its beat count. The N-gram profile of a collection of chord sequences is the simple average of the N-gram profile of all the chord seq...

In this study, we examined the pronunciation characteristics of multiword expressions (MWEs). We first drew up an inventory of frequently occurring N-grams extracted from orthographic transcriptions of spontaneous speech contained in a large corpus of spoken Dutch. For about 10% of these Ngrams phonetic transcriptions were available, which were examined. Our results show that the pronunciation ...

This paper describes an automatic, context-sensitive, word-error correction system based on statistical language modeling (SLM) as applied to optical character recognition (OCR) postprocessing. The system exploits information from multiple sources, including letter n-grams, character confusion probabilities, and word-bigram probabilities. Letter n-grams are used to index the words in the lexico...

This paper presents a new approach for finding the best ngrams that efficiently summarize a large set of reviews. The proposed unsupervised method uses a readability score and a representativeness score to select those n-grams that best convey the main opinions contained in the processed reviews. In order to further refine the selected n-grams, we use sentiment analysis and part of speech (POS)...

Paraphrase recognition consists in detecting if an expression restated as another expression contains the same information. Traditionally, for solving this prob­ lem, several lexical, syntactic and semantic based tech­ niques are used. For measuring word overlapping, most of the works use n-grams; however syntactic n-grams have been scantily explored. We propose using syntac­ tic dependency and...

Authorship attribution studies consider author's identification of an anonymous text. This is a long history problem with a great number of various approaches. Those ones based on n-grams single out by their performances and good results. A n-gram approach is language independent but the selection of a number n is actually not. The focus of this paper is determination of a set of optimal values...

In the process of establishing the information theory, C. E. Shannon proposed the Markov process as a good model to characterize a natural language. The core of this idea is to calculate the frequencies of strings composed of n characters (n-grams), but this statistical analysis of large text data and for a large n has never been carried out because of the memory limitation of computer and the ...

This work presents a generalized approach for the fast structural alignment of thousands of macromolecular structures. The method uses string representations of a macromolecular structure and a hash table that stores n-grams of a certain size for searching. To this end, macromolecular structure-to-string translators were implemented for protein and RNA structures. A query against the index is p...

Anticancer peptides (ACPs) are short protein sequences; they perform functions like some hormones and enzymes inside the body. The role of any or peptide is related to its structure sequence amino acids that make up it. There 20 types in humans, each them has a particular characteristic according chemical structure. Current machine deep learning models have been used classify ACPs problems. How...