Automatic Genre Classification as a Study of the Viability of High-Level Features for Music Classification
نویسنده
چکیده
This paper examines the potential of high-level features extracted from symbolic musical representations in regards to musical classification. Twenty features are implemented and tested by using them to classify 225 MIDI files by genre. This system differs from previous automatic genre classification systems, which have focused on low-level features extracted from audio data. Files are classified into three parent genres and nine sub-genres, with average success rates of 84.8% for the former and 57.8% for the latter. Classification is performed by a novel configuration of feed-forward neural networks that independently classify files by parent genre and sub-genre and combine the results using weighted averages.
منابع مشابه
شناسایی خودکار سبک موسیقی
Nowadays, automatic analysis of music signals has gained a considerable importance due to the growing amount of music data found on the Web. Music genre classification is one of the interesting research areas in music information retrieval systems. In this paper several techniques were implemented and evaluated for music genre classification including feature extraction, feature selection and m...
متن کاملAutomatic classification of Non-alcoholic fatty liver using texture features from ultrasound images
Background: Accurate and early detection of non-alcoholic fatty liver, which is a major cause of chronic diseases is very important and is vital to prevent the complications associated with this disease. Ultrasound of the liver is the most common and widely performed method of diagnosing fatty liver. However, due to the low quality of ultrasound images, the need for an automatic and intelligent...
متن کاملMultiexpert System for Automatic Music Genre Classification
Automatic classification of music pieces by genre is one of the crucial tasks in music categorization for intelligent navigation. In this work we present a multiExpert genre classification system based on acoustic, musical and timbre features. A novel rhythmic characteristic, 2D beat histogram is used as high-level musical feature. Timbre features are extracted by multiple-f0 detection algorith...
متن کاملGenre Classification based on Predominant Melodic Pitch Contours
We present an automatic genre classification system based on melodic features. First a ground truth genre dataset composed of polyphonic music excerpts is compiled. Predominant melodic pitch contours are then estimated, from which a series of descriptors is extracted. These features are related to melody pitch, variation and expressiveness (e.g. vibrato characteristics, pitch distributions, con...
متن کاملAutomatic Identification and Classification of the Iranian Traditional Music Scales (Dastgāh) and Melody Models (Gusheh): Analytical and Comparative Review on Conducted Research
Background and Aim: Automatic identification and classification of the Iranian traditional music scales (Dastgāh) and melody models (Gusheh) has attracted the attention of the researchers for more than a decade. The current research aims to review conducted researches on this area and consider its different approached and obstacles. Method: The research approach is content analysis and data col...
متن کامل