Musical genres are categorical descriptions that are used to describe music. They are commonly used to structure the increasing amounts of music available in digital form on the Web and are important for music information retrieval. Genre categorization for audio has traditionally been performed manually. A particular musical genre is characterized by statistical properties related to the instr...

Genres of spoken and written texts are being intensively studied from various angles, e.g., communication studies, discourse analysis, computational linguistics, without arriving at a generally accepted definition. Many corpora have been built to represent the language, but very few large corpora indicate genres, and when they do the typology of genres varies widely. For instance, the Brown cor...

Constructing robust categorical and typological classifiers, i.e., finding auditory constructs utilized for describing music categories, is an important problem in music genre classification. Supervised methods such as support vector machine (SVM) achieve state of the art performance for genre classification but suffer from over-fitting on training examples. In this paper, we introduce a superv...

Recently a large amount of new chord annotations have been made available. This raises hopes for further development in automatic chord estimation. While more data seems to imply better performance, a major challenge however, is the wide variety of genres covered by these new data. As a result, the genre-independent training scheme as is common today is bound to fail. In this paper we investiga...

Automatic classification of music genre is widely studied topic in music information retrieval (MIR) as it is an efficient method to structure and organize the large numbers of music files available on the Internet. Generally, the genre classification process of music has two main steps: feature extraction and classification. The first step obtains audio signal information, while the second one...

Digital music distribution industry has seen a tremendous growth in resent years. Tasks such us automatic music genre discrimination address new and exciting research challenges. Automatic music genre recognition involves issues like feature extraction and development of classifiers using the obtained features. As for feature extraction, we base on Self-Organizing Maps to map the high-dimension...

This paper examines automated genre classification of text documents and its role in enabling the effective management of digital documents by digital libraries and other repositories. Genre classification, which narrows down the possible structure of a document, is a valuable step in realising the general automatic extraction of semantic metadata essential to the efficient management and use o...

In my thesis, I examine the discursive space of the detective fiction genre following Kasai Kiyoshi’s periodization in his two-volume seminal work Tantei shōsetsuron (The Theory of Detective Fiction, 1998). I investigate how Japanese detective fiction has developed in relation to Japan’s modernization, industrialization, nationalism, and globalization, specifically in the 1920s-30s, the 1950s-6...

English language teaching (ELT) writing practitioners have long attempted to improve EFL/ESL learners’ competence in writing with recourse to either instruction or feedback. Likewise, researchers have, to date, mainly focused on either of these treatments to enhance language learners’ composing ability. Which treatment leads to more significant improvements is, however, unclear. Moreover, of th...

A software system that automatically classifies MIDI files into hierarchically organized taxonomies of musical genres is presented. This extensible software includes an easy to use and flexible GUI. An extensive library of high-level musical features is compiled, including many original features. A novel hybrid classification system is used that makes use of hierarchical, flat and round robin c...