We investigate the uses and limitations of MFCC analysis for feature extraction from music files in the domain of genre recognition. Intra-genre and Inter-genre classification is explored. We implement a method of genre classification based on MFCC extraction, K-means clustering, and KNN analysis. We demonstrate the efficacy of our method through testing, yielding a 99% accuracy rate.

This paper contributes to a facet from the area of Web Information Retrieval that has recently received much attention: The satisfaction of a user’s personal information need with respect to text type, presentation type, or information quality. We imply that such properties can be quantified for all kinds of Web documents, and we subsume them under the term “Web genre” or “genre”. Recent survey...

Abstract There is very little research on the use of metadiscourse markers in abstracts across different disciplines (especially a single study) undergraduates as novice researchers, and qualitative has been done topic EFL ESL contexts altogether. Thus, purpose this study to examine undergraduates’ social sciences three (English Language Communication, Mass Psychology) Faculty Social Sciences L...

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...

Although scientific forum has obliged its members to hide their presence particularly while they are discussing research outcomes to avoid personal biases, a recent trend is encouraging writers to demonstrate their identity as the author of the text through the use of first person pronouns in order to take responsibility for the content. Therefore, the present study focuses on intermediate and ...

Despite questions having a long-standing history in theoretical linguistics, the interface between empirically grounded corpus linguistics of questioning behaviour and analytically driven pragmatic theory question structure context has received significantly less attention. This paper aims to contribute this field research by showing that four-way categorisation into types, namely, pure questio...

This paper presents PROVERB a text planner for argumentative texts. PROVERB ś main feature is that it combines global hierarchical planning and unplanned organization of text with respect to local derivation relations in a complementary way. The former splits the task of presenting a particular proof into subtasks of presenting subproofs. The latter simulates how the next intermediate conclusio...

Most formal approaches to argumentative reasoning under uncertainty focus on the analysis of qualitative aspects. An exception is the framework of probabilistic argumentation systems. Its philosophy is to include both qualitative and quantitative aspects through a simple way of combining logic and probability theory. Probabilities are used to weigh arguments for and against particular hypothese...