Genre Classification Research Articles

Music genre classification based on fusing audio and lyric information

Music genre classification based on fusing audio and lyric information

Jazz in the context of «global village» principle

This article addresses one of the manifestations of interaction between different music domains, using the sphere of jazz as an example. In the course of evolution, the art of music has developed five relatively independent domains based on fundamentally different principles of musical thought. Globalization, which has intensified in the 20th century and continues to grow in the 21st, gave birth to a new domain called by us “unionique music”. This domain is the object of our research. The relevance of this study stems from the fact that unionique music compositions do not fit the standard principles of genre classifications used by academic music scholars. At the same time, an important feature that unites these compositions is the combination of such spheres of music as jazz, rock, “traditional” music of Western European academic tradition, ethnic music and folklore. Nevertheless, the degree of impact of a particular music domain in different compositions has different indicators. This article focuses on the analysis of unionique music compositions that contain expressive means of various domains, but at the same time are founded on the jazz-based principle of music playing.

The world of things in traditional Chinese painting

The relevance of the article. The formation of genre and the principles of genre classification in the art of East Asian countries is one of the least researched problems in the theory and history of art. It is generally accepted that still life appeared in the art of China as a result of the influence of the Euro-pean artistic system. Meanwhile, motifs related to the depiction of elements of the subject environment can be traced in other genres of Chinese painting. In modern artistic practice, still life is considered mainly as an element of academic education, but its creative potential remains little realized. Therefore, the relevance of the research is determined by the needs of both theory and artistic practice.
 The purpose of the article is to determine the main approaches to the depiction of things, their typological complexes, their role and significance in Chinese classical art.
 The methodology. In the research we used general scientific and special research methods. In particular, methods of systematization, content analysis and typology were applied; methods of formal, stylistic, semantic, comparative analysis.
 The results. The article outlines the main approaches to studying the origins of still life as a genre in the Chinese artistic tradition. As a result of the analysis of samples of easel and decorative painting, the main models of the representation of things were revealed, their typology, role and means of representation in the visual and content structure of the works were determined. The semantic aspects of pictorial motifs and their connections with the development of handicrafts, Confucian education, tastes and values of the privileged top of society and the development of collecting, are highlighted.
 The scientific novelty. For the first time, in the work we touched upon the issue of the formation of still life as a genre and its origins in Chinese painting, highlighted the previous artistic experience of depicting objects of the material environment, defined the main thematic complexes, established their role and significance in classical works.
 The practical significance. The results of the research can be used in the development of educational courses in the history of art and provide the necessary material both for creative experiments and for the development of various projects in the field of visual arts.
 Conclusions. The results of the analysis of various materials of fine art allow us to claim that in Chinese classical art, other, different from European, options for the representation of the world of things were formed. Typologically, they are represented by three models: a “portrait” of a thing (a close-up of one object with a careful depicting of form and decoration), a thing as a component of a portrait, a catalogue of things (a decorative composition on the theme “4 treasures of a scientist”, “4 noble arts”, “100 antiquities”). In all models, the depicted objects act as personifications of material and spiritual values of society, a sign of Confucian virtues, and as benevolent symbols. The “100 antiquities” complex, which was formed by XVIII century, combined previous lists of valuable things and became a reflection of craft achievements, educational tradition and awareness of its value, and the development of collecting.

Comparative Analysis of KNN, Naïve Bayes and SVM Algorithms for Movie Genres Classification Based on Synopsis.

Text classification is a process of categorizing a text into the correct label. Text classification in natural language processing is a challenging task that requires accuracy to get the correct results, manual text classification tends to be inefficient because it requires a lot of time and also experts. The utilization of machine learning for automatic text classification can be a solution to this problem. KNN, Naive Bayes, and SVM are known as some of the most algorithms to solve classification problems, especially text classification. In this study, we are trying to compare the KNN, Naive Bayes, and SVM algorithms for text classification with the problem of classifying movie genres based on a synopsis using datasets obtained from Kaggle.com and IMDB Dataset. The results of this study indicate that of the 12 experiments, Support Vector Machine (SVM) is the bestperforming algorithm with an accuracy of 90%, 93%, 65%, and 63%. It is hoped that this research can help to determine the best algorithm in the text classification process.

Popular Song Topics in the Dutch Republic

This article investigates popular topics and topical fluctuations in a diachronic corpus of 43,772 Dutch songs, all written between 1550 and 1750, contained within the Dutch Song Database. Computational methods such as topic modelling are used to analyse the relationship between topical changes and cultural-historical developments. Two cultural trends are used as case studies: the role of Petrarchism, and the articulation of a patriotic identity in early modern Dutch song culture. Furthermore, this data-driven approach reveals how subcategories can be defined within the existing but incomplete genre classification in the song collection. The results obtained contribute to a better understanding of the richness of the Dutch Song Database, and will facilitate the use of the song collection by future users.

Classification of Russian Texts by Genres Based on Modern Embeddings and Rhythm

The article investigates modern vector text models for solving the problem of genre classification of Russian-language texts. Models include ELMo embeddings, BERT language model with pre-training and a complex of numerical rhythm features based on lexico-grammatical features. The experiments were carried out on a corpus of 10,000 texts in five genres: novels, scientific articles, reviews, posts from the social network Vkontakte, news from OpenCorpora. Visualization and analysis of statistics for rhythm features made it possible to identify both the most diverse genres in terms of rhythm: novels and reviews, and the least ones: scientific articles. Subsequently, these genres were classified best with the help of rhythm features and the neural network-classifier LSTM. Clustering and classifying texts by genre using ELMo and BERT embeddings made it possible to separate one genre from another with a small number of errors. The multiclassification F-score reached 99%. The study confirms the efficiency of modern embeddings in the tasks of computational linguistics, and also allows to highlight the advantages and limitations of the complex of rhythm features on the material of genre classification.

Developing Music Recommendation System by Integrating an MGC with Deep Learning Techniques

In the modern scenario, everyone uses the internet to find music, movies, products, services and other commodities on a regular basis to make their lives easier. Because of a lot of data on millions of music, movie, products and services on websites, we need a recommender system very much to assist people in making decisions more quickly and easily. In this research study, we have developed an intelligent music recommendation system by integrating a Music Genre Classification (MGC) with different types of Deep Learning Techniques such as RNN-LSTM, GRU and CNN. We have used the GTZAN Genre dataset to training our system. We have extracted the features from GTZAN dataset by the help of Mel Frequency Cepstral Coefficients (MFCCs) then pass the MFCCs into our deep learning networks. After classifying the appropriate music genre, recommended the music from particular genre from the labelled database which has been classified by our system. From our proposed models the GRU, CNN and RNN-LSTM produced about 71%, 72% and 74% respectively in our testing accuracy. The RNN-LSTM has achieved the best accuracy result (74%) among all of our proposed models.

Cinema 21 Movie Trailer Catalog Application Android Based

In this global era, the internet has penetrated various fields such as social, advertising, and business. With a large number of films, a film genre classification is made to assist users in finding and selecting the right films to watch. The genre in the film is the main element in a recommendation system, because with the classification of genres it can make it easier for the system to search for a film based on certain types. The string matching method, which is part of the string search process, plays an important role in getting documents that match your information needs more quickly. Simply by using a smartphone and internet access, people can enjoy various information on movie trailers. Then the problem is formulated how to make an android-based cinema 21 movie trailer catalog application with a string matching algorithm. Can improve better service to consumers, where consumers are expected to be able to access online so that consumers can find out information about movie trailers on the application.

Robust handcrafted features for music genre classification

Robust handcrafted features for music genre classification

Bava & Leone: The “Spaghettification” of the American Cinematic Form

In the 1960s two Italian filmmakers, Mario Bava and Sergio Leone, released a string of notable films that directly challenged and re-framed the revered American genres of horror and the western respectively. Their revisualization and ultimate reinterpretation of these traditional genres reached its zenith with the release of Bava’s Black Sabbath (1963) and Leone’s Once Upon a Time in the West (1968). They marked the dawn of a “spaghettification” of the American cinematic form.
 This paper argues that the “spaghettification” of the horror and western genres within Black Sabbath and Once Upon a Time in the West redefined the visual calculus of these American genres and revitalized their core tenets, cementing a new cinematic approach to them. Their use of cinematic close-ups, operatic scores, technicolour cinematography, and subversion of the American icon through the casting of Boris Karloff and Henry Fonda established a bold new cinematic style that reshaped the classic American form. This analysis will also note that the motivation behind this visual reformulation was wholly divergent, as Bava embraced his low-budget circumstances to relish the absurdity inherent in the horror genre, while Leone sought to establish a “New West” that was emblematic of the violence and bigotry of the American frontier. The cinematic style of these two films were primarily motivated by a love for the American classics and their revitalization of these classic genres would permeate in the minds of many budding auteurs such as Quentin Tarantino and Martin Scorsese, who in turn would go on to further rejuvenate the American cinematic landscape.
 Keywords: Sergio Leone, Mario Bava, Western, Horror, Italian, American, Cinema

Machine Learning Based Music Genre Classification and Recommendation System

Music has an important role in our life. It is also known that music helps to relax and strengthen the human spirit. The widespread use of the Internet has led to significant changes and developments in the music industry. The increase and widespread use of online music listening and sales platforms, the constant updating of these platforms and the classification of music genres can be given as examples of these developments. Music genre classification is an important step for the music recommendation system. In order for music to be classified by individuals require to listen to many songs and choose their genre. This is a difficult process and waste of time. In this paper, it is aimed to classify music according to its genres by using machine learning algorithms and to suggest similar types of music to the user. For this purpose, the features of the music files were extracted with digital signal processing techniques, and the music genres were automatically detected by using machine learning algorithms with the obtained features and a recommendation system was developed. The GTZAN dataset was chosen to be used in the study. Eight different machine learning models were trained in the Jupyter Notebook environment and the findings were compared. For this purpose, the data set was split into two sets as 80% training and 20% testing, and the accuracy of the models was evaluated. Among the tested models, the most successful result was obtained with the XGBoost algorithm with an accuracy rate of 91,792%.

Reading Anna Frajlich's Latest Volume of Poetry

Reading Anna Frajlich's Latest Volume of Poetry

A two-stage gap safe screening rule for multi-label optimal margin distribution machine

Multi-label optimal margin distribution machine (mlODM) is an efficient algorithm for multi-label classification. Although it can achieve great generalization performance, it is inefficient for large-scale datasets due to the huge number of label pairs. Motivated by its sparse solution, in this paper, we propose a two-stage gap safe screening rule for accelerating mlODM, termed as TSSR. First, a sequential safe screening rule (SSSR) based on gap is designed to screen out part of redundant label pairs prior to training, which reduces the scale of mlODM. Compared with the previous DVI rule, our method ensures absolute safety without destroying efficiency. In the second stage, to further speed up the solving process, a dynamic safe screening rule (DSSR) is embedded into the solving algorithm DCDM when training the simplified mlODM. More importantly, the feasible solution generated in the first stage can promote the efficiency of DSSR. To the best of our knowledge, this is the first attempt to create a hybrid screening rule for multi-label model. Our TSSR can greatly reduce the cost and achieve exactly the same accuracy. Experimental results on seven multi-label benchmark datasets and two real-world learning problems including movie genres classification and hypoglycemic drugs prediction verify the superiority of the proposed methods.

Ghana

Among African countries where hip hop has a strong presence, Ghana is an interesting case study in the relationship between hip hop and afrobeats. Ghana has benefitted from the popularity of afrobeats, with several Ghanaian artists releasing collaborations with international artists. Many Ghanaian hip hop artists have also been helped by the relationship between Ghana and the African diaspora and leveraged that relationship into a successful rap career. An examination of hip hop in Ghana requires a consideration of genre classification in a music scene where hip hop and afrobeats often intersect. It also requires a consideration of the historical relationship between Ghana and the African diaspora, which has been strengthened in the wake of the 2019 Year of Return. Ghana’s relationship to the African diaspora has influenced the development of music genres in the country. The arrival of hip hop in Ghana especially influenced the development of hiplife and then afrobeats. Ghanaian hip hop maintains its own identity, while at the same time sharing an identity with hiplife and afrobeats. Ghana is not the only country where hip hop and pop music share a close relationship, but one cannot study Ghanaian hip hop without also studying Ghanaian hiplife or afrobeats. Because of the close relationship between hip hop, hiplife and afrobeats, this contribution includes a discussion of the latter two, along with a discussion of the roles that genres play, both from a music standpoint and from a marketing standpoint.

Late Modernist Noirs: Béla Tarr’s Damnation/ Kárhozat and György Fehér’s Passion/ Szenvedély

"Since the 80s, a large number of films, manifestly indebted to the classic American noir films of the 40s and 50s, have been appropriately labeled neo-noirs. An interesting, but less well documented version of this phenomenon, mostly American in its nature, is the case of some of the films belonging to the so-called Hungarian “Black Series”. Made at the end of the 80s and during the 90s, these films are modernist, stylized versions of the classic noir films. This essay tries to give an outline of this East European reappraisal of the noir film, by insisting on the narrative and aesthetical strategies used by directors such as Béla Tarr or György Fehér in order to deconstruct the classical genre."

The Work of Maryna Denysenko for the Instrumental Bandura Performance: The Aspects of Timbre and Sonority

This study considers modern instrumental and vocal-instrumental bandura performance with regard to the aspects of timbre and sonority. The latter influence innovative experiments in the field of bandura performance the most. Modern instrumental compositions for bandura are marked by the expansion ofstylistic attributes; the use of a wide range of new techniques and elements of polystylistics, classical genre prototypes, and the most recent technologies (aleatorics, cluster, layered polyphony, sonorism, etc.). These explorations are also characterized by a deeply individual artist’s idea, marked by innovative discoveries in the bandura technique, often determined by the timbre and sound concept of the composition. It should be noted that the bandura in its modern form (namely, Chernihiv and Lviv chromatic prototypes) is a relatively new instrument. It has undergone a significant transformation over the centuries: from an accompanying one to an instrument with a broad expressive potential for genre and stylistic solutions in interpreting the stylistic discourses. Its dynamic development is evident in recent decades, when bandura, because of its timbre and dynamic potential, happened to be on the forefront of the innovative compositional explorations with experimental techniques and approaches. The increased attention of composers to the sound of the bandura, its diversity, changeability, length, etc. encourages performers and composers to experiment with the innovative ways of bandura sound-producing. The well-known Ukrainian composer Maryna Denysenko (1962–2022) worked productively in this direction. Her work testifies to the attention to timbre and sonorous expressiveness along with expanding and changing the emphasis on the traditional approaches to the bandura performing. In her works, Denysenko significantly modernizes the expressive and performing potential of the bandura performance, while at the same time modifying established ideas about the genre models of bandura art and the field of timbre/ sonority of academic bandura.

Urdu Ethics Literature and the Diversity of Muslim Thought in Colonial India

Abstract This essay discusses Urdu-language akhlaq (ethics) texts produced and circulated in late-colonial India (1858–1947), situating them both within a classical genre of Islamic ethics and in the context of Indian vernacular print culture. It focuses on three akhlaq texts published between the 1870s and 1930s to consider contemporary Muslim ethical concerns and schema, arguing that the genre points to a widespread, everyday, and unexceptional Muslim subjectivity that placed a high value on ethical striving. The essay offers new perspectives on the history of Muslims in late-colonial India by highlighting a non-institutional, diffuse, and capacious intellectual formation whose ideas were disseminated through print in a commercial market. It also expands existing notions of Muslim authority from individuals—such as the ulama (Muslim clerical class)—and institutions—such as madrasas (religious schools and seminaries)—to include literary genres themselves. Finally, the article broadens the range of Muslim subject-positions represented in scholarship on Islam in colonial India.

Am I a Resource-Poor Language? Data Sets, Embeddings, Models and Analysis for four different NLP Tasks in Telugu Language

Due to the lack of a large annotated corpus, many resource-poor Indian languages struggle to reap the benefits of recent deep feature representations in Natural Language Processing (NLP) . Moreover, adopting existing language models trained on large English corpora for Indian languages is often limited by data availability, rich morphological variation, syntax, and semantic differences. In this paper, we explore the traditional to recent efficient representations to overcome the challenges of a low resource language, Telugu. In particular, our main objective is to mitigate the low-resource problem for Telugu. Overall, we present several contributions to a resource-poor language viz. Telugu. (i) a large annotated data (35,142 sentences in each task) for multiple NLP tasks such as sentiment analysis, emotion identification, hate-speech detection, and sarcasm detection, (ii) we create different lexicons for sentiment, emotion, and hate-speech for improving the efficiency of the models, (iii) pretrained word and sentence embeddings, and (iv) different pretrained language models for Telugu such as ELMo-Te , BERT-Te , RoBERTa-Te , ALBERT-Te , and DistilBERT-Te on a large Telugu corpus consisting of 8,015,588 sentences (1,637,408 sentences from Telugu Wikipedia and 6,378,180 sentences crawled from different Telugu websites). Further, we show that these representations significantly improve the performance of four NLP tasks and present the benchmark results for Telugu. We argue that our pretrained embeddings are competitive or better than the existing multilingual pretrained models: mBERT , XLM-R , and IndicBERT . Lastly, the fine-tuning of pretrained models show higher performance than linear probing results on four NLP tasks with the following F1-scores: Sentiment (68.72), Emotion (58.04), Hate-Speech (64.27), and Sarcasm (77.93). We also experiment on publicly available Telugu datasets (Named Entity Recognition, Article Genre Classification, and Sentiment Analysis) and find that our Telugu pretrained language models ( BERT-Te and RoBERTa-Te ) outperform the state-of-the-art system except for the sentiment task. We open-source our corpus, four different datasets, lexicons, embeddings, and code https://github.com/Cha14ran/DREAM-T. The pretrained Transformer models for Telugu are available at https://huggingface.co/ltrctelugu.

Machine Learning for Music Genre Classification Using Visual Mel Spectrum

Music is the most convenient and easy-to-use stress release tool in modern times. Many studies have shown that listening to appropriate music can release stress. However, since it is getting easier to make music, people only need to make it on the computer and upload it to streaming media such as Youtube, Spotify, or Beatport at any time, which makes it very infeasible to search a huge music database for music of a specific genre. In order to effectively search for specific types of music, we propose a novel method based on the visual Mel spectrum for music genre classification, and apply YOLOv4 as our neural network architecture. mAP was used as the scoring criterion of music genre classification in this study. After ten experiments, we obtained a highest mAP of 99.26%, and the average mAP was 97.93%.

Религиозный стиль как система жанров (Рец. на кн.: Ицкович Т. В. Жанровая система религиозного стиля [Текст] : монография / Т. В. Ицкович. – М. : ФЛИНТА, 2021. – 400 с.)

The review is a response to the publication of T. V. Itskovich’s monograph “Genre system of the religious style”. The author of the book presents an original view on the functional religious style as a system of genres and gives its multidimensional description. The relevance of the research is justified by the need for a comprehensive linguistic study of the religious style as part of the paradigm of functional varieties of the modern Russian literary language and the classification of genres of the religious style on a single basis. In the monograph, its author, basing on an integrated approach which combines communicative-pragmatic and categorical-textual aspects of the study of religious texts, taking into account the cultural-historical and textual genesis of religious genres, establishes the constructive principle of the religious style, gives a scientific description of the system of religious genres and its proto-genre basis, reveals the compositional-thematic and speech originality of religious genre types and their varieties as well as the core and periphery of the genre field of religious style. The study is based on the texts of the liturgical and non-liturgical spheres of Orthodox religious communication in Russian and Church Slavonic, selected by the author on the basis of the tradition of their use in the religious activities of the Church and the individual as well as the frequency of their use in modern religious communication.