Music Genre Classification is one of the most active tasks in Music Information Retrieval (MIR). Many successful approaches can be found in literature. Most of them are based on Machine Learning algorithms applied to different audio features automatically computed for a specific database. But there is no computational model that explains how musical features are combined in order to yield genre...

In this paper, I propose a refined and incremental centroid-based approach for genre categorization of web pages. My approach is based on the construction of genre centroids using a set of training web pages. These centroids will be used to classify new web pages. The originality of my approach is the implementation of two new aspects, which are refining and incrementing. My approach is based o...

Documents on the Web can be composed of multiple Web pages, suggesting the need to consider how linking between pages affects a document’s form. We illustrate this point by considering patterns of linking in a common genre of document, the Frequently Asked Questions file or FAQ. In a sample of 70 FAQs, we found four patterns of linking: no links, links within the page, links to pages on the sam...

This paper presents a corpus-based study on syncopation patterns in ragtime. We discuss open questions on the ragtime genre and the potential of computational tools in addressing these questions, contributing to the fields of Musicology and Music Information Retrieval (MIR), and giving back to the ragtime enthusiasts community. We introduce the RAG-collection of around 11000 ragtime MIDI files ...

We investigate the problem of automated video classification by analysing the low-level audio-visual signal patterns along the time course in a holistic manner. Five popular TV broadcast genre are studied including sports, cartoon, news, commercial and music. A novel statistically based approach is proposed comprising two important ingredients designed for implicit semantic content characterisa...

The previous chapter reviewed three traditions of genre studies, namely, the new rhetoric, systemic functional and ESP perspectives on genre. While new rhetoric genre analyses focus on the interrelation between text and context and SFL genre studies stress the linguistic analysis of text, ESP approaches to genre take an approach that is some way between these two. This chapter extends the discu...

Automatic music genre classification is one of the most challenging problems in music information retrieval and management of digital music database. In this paper, we propose a new method to classify music genres using text categorization methods. Differing from previous solutions which were mainly based on analysis on acoustic or symbolic audio signal, here we consider music as a text-like se...

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space def...

Genre conventions emerge across discourse communities over time to support the communication of ideas and information in socially and cognitively compatible forms. Digital genres frequently borrow heavily from the paper world even though the media are very different. This research sought to identify the existence and form of a truly digital genre. Preliminary results from a survey of user perce...

this study aims at uncovering the effect(s) of genre-based instruction (gbi) on listening proficiency among iranian efl learners. moreover, it seeks to explore the relationship between effectiveness of gbi and listening proficiency. for this purpose, 68 efl learners in two different groups at zabol university were selected. group a included 30 participants (12 males and 18 females), and group b...