Existing systems for automatic genre classification follows a supervised framework that extracts genre-specific information from manually-labeled music data and then identifies unknown music data. However, such systems may not be suitable for personal music management, because manually labeling music based on individually-defined genres can be labor intensive and subject to inconsistence from t...

In this paper we would like to contribute to the discussion about genre-enabled applications, currently engaging many genre researchers, by presenting a preliminary assessment of a web add-on devised to augment the result list of general-purpose search engines with genre labels. For this assessment, we use a small collection of web pages manually annotated with genre labels by a large number of...

In this paper, we propose an implementable characterization of genre suitable for automatic genre identification of web pages. This characterization is implemented as an inferential model based on a modified version of Bayes’ theorem. Such a model can deal with genre hybridism and individualization, two important forces behind genre evolution. Results show that this approach is effective and is...

This research explores the clustering of songs using lyrics features grouped into similar classes and heterogeneous combinations. Simple techniques are used to extract 140 features for analysis with Kohonen self-organising maps. These maps are evaluated using visual analysis and objective measures of validity with respect to the clustering of eight hand-selected song pairs. According to gold st...

This paper discusses an approach for the feature extraction for audio genre classification and many other tasks of music information retrieval (MIR). Many musical genres are characterized not only by timbral information but also by temporal features such as rhythm patterns and bass-line patterns. In particular, modern music pieces mostly have certain fixed rhythm and bass-line patterns per genr...

Cepstral analysis is effective in separating source from filter in vocal and monophonic [pitched] recordings, but is it a good general-purpose framework for working with music audio? We evaluate covariance in spectral features as an alternative to means and variances in cepstral features (particularly MFCCs) as summaries of frame-level features. We find that spectral covariance is more effectiv...

1 – Introduction In this work, we are presenting our approach to automatic genre classification for music files, or songs, which consists of audio files represented by a time series data, where the goal is to automatically process the files, to establish a genre assignment. Such applications that require automatic genre classification include internet radio stations that play similar songs base...

Textbooks considered as one of the most important genres of academic writings would guarantee effective teaching and learning in EFL/ESL courses. Since textbooks are gaining more and more importance, the knowledge of their rhetorical organization that provides learners and teachers with efficient use of their content seems necessary. This article describes the rhetorical organization of the tex...

Acquiring proficiency in academic genres is a key factor in research community. Among various genres in academic discourse communities, spoken genre, especially Conference Presentations (CPs), play a crucial role in research communities, though investigation on this important genre is in its infancy or is relatively under-researched. Therefore, the present study aims to shed light on the import...