This article presents two experiments investigating the degree to which listeners can detect changes in melodies. In both studies, pairs of melodies were presented to a group of professional musicians and a group of non-musicians. In Experiment 1, musical structure and musical expertise were explored with stylistic, non-stylistic, and random melodies. Experiment 2 utilized a full-factorial desi...

Stylometry is the study of the computational and mathematical properties of style. The aim of a stylometrist is to derive stylometrics and models based upon those metrics to quantitatively gauge stylistic propensities. This paper presents a method of formulating a stylistic distance function via a weighted ratio of lexical stylometrics, the higher the ratio the more the styles diverge. The coef...

Computer-supported authorship attribution provides tools for extracting stylistic features that can help verify or identify the author of text documents. In many situations finding the author of a document is very important, such as the detection of plagiarism for protecting copyrights and forensic support during criminal investigations. This paper, thus explores a novel stylistic feature with ...

In this paper we describe a novel feature discovery technique that can be used to model stylistic variation in sociolects. While structural features offer much in terms of expressive power over simpler features used more frequently in machine learning approaches to modeling linguistic variation, they frequently come at an excessive cost in terms of feature space size expansion. We propose a nov...

This paper analyzes what stylistic characteristics differentiate different styles of writing, and specifically types of different A-level computer science articles. To do so, we compared various full papers using stylistic feature sets and a supervised machine learning method. We report on the success of this approach in identifying papers from the last 6 years of the following three conference...