Multimedia Recognition of Piano Music Based on the Hidden Markov Model

Piano performance is an art with rich artistic elements and unpredictable performance skills. It is an important carrier for playing beautiful piano sounds. The generation of musical tension and expression of piano performance is a vivid display of piano performance skills. In piano performance, we should pay attention to the cultivation and flexible application of performance skills. In order to ensure the richness and artistry of piano performance, it is fully based on the artistic characteristics of piano performance. Through in-depth analysis of the principle of the hidden Markov model, it is applied to the multimedia recognition process of piano playing music. In the process of obtaining the template, the fundamental frequency of the piano playing music differs greatly, and the piano playing music appears during the performance process. For the problem of low recognition rate, this paper proposes a multimedia recognition method for piano music. Finally, the analysis of experimental results shows that the method proposed in this paper has a 16% higher recognition rate than the traditional method, and it has a certain value in the multimedia recognition of piano music.

Popular Song Composition Based on Deep Learning and Neural Network

For the general public, composition appears to be professional and the threshold is relatively high. However, automatic composition can improve this problem, allowing more ordinary people to participate in the composition, especially popular music composition, so the music becomes more entertaining, and its randomness can also inspire professionals. This article combines deep learning to extract note features from the demonstration audio and builds a neural network model to complete the composition of popular music. The main work of this paper is as follows. First, we extract the characteristic notes, draw on the design process of mel-frequency cepstral coefficient extraction, and combine the characteristics of piano music signals to extract the note characteristics of the demonstration music. Then, the neural network model is constructed, using the memory function of the cyclic neural network and the characteristics of processing sequence data, the piano notes are combined into a sequence according to the musical theory rules, and the neural network model automatically learns this rule and then generates the note sequence. Finally, the ideal popular piano music scores are divided into online music lover scores and offline professional ratings. The score index is obtained, and each index is weighted by the entropy weight method.

Charakterystyka wczesnej reklamy pandemicznej

The aim of this paper is to examine early pandemic commercials and show the main changes in their focus from the point of view of communication. In terms of the contents, COVID-19 lockdown, heroism of health care workers, social distancing, online learning, remote work, and the strong shift towards online communication are underlined with an enormous stress put on such values as family, helping each other and being together in these difficult times. Characteristic nonverbal components of commercials referring to the pandemic situation include, for example, sentimental piano music, dimmed colours, a specific style of filming, or showing ordinary people as actors. Finally, it is noticed that some ad makers decide to use the sense of humour in their spots. In conclusion, the coronavirus pandemic and its effects can be easily observed on every level of an advertising message.

Guiding Hand

The emergence of imaginative children’s music in the second half of the nineteenth century reframed the relationship between children and music in revolutionary ways. The dominant paradigm had been for children to repetitiously practice mechanistic exercises, a time-consuming occupation that the German composer Robert Schumann considered particularly wasteful and tasteless. In response he composed Album für die Jugend in 1848, a collection of children’s pieces that utilised a combination of text, picture and music to appeal to the interests of children, and to inspire their enthusiasm for musical play. Schumann envisioned his music as an extension of familial nurturance, which played a powerful role in directing children towards a musically and spiritually rich adulthood. As the tradition of imaginative children’s music developed during the nineteenth century, the dual themes of entertainment and education remained central to its generic identity, and continued to speak to the significance of piano music as a tool for the socialisation of children. The work of Jacqueline Rose offers a lens through which to explore this music’s manipulative influence upon children. The multimodal and performative characteristics of these musical pieces demonstrate the hidden influence of the adult’s guiding hand and the dire consequences that come to those who transgress musical and social boundaries.

Design of the Piano Score Recommendation Image Analysis System Based on the Big Data and Convolutional Neural Network

In the era of big data, the problem of information overload is becoming more and more obvious. A piano music image analysis and recommendation system based on the CNN classifier and user preference is designed by using the convolutional neural network (CNN), which can realize accurate piano music recommendation for users in the big data environment. The piano music recommendation system based on the CNN is mainly composed of user modeling, music feature extraction, recommendation algorithm, and so on. In the recommendation algorithm module, the potential characteristics of music are predicted by the regression model, and the matching degree between users and music is calculated according to user preferences. Then, music that users may be interested in is generated and sorted in order to recommend new piano music to relevant users. The image analysis model contains four “convolution + pooling” layers. The classification accuracy and gradient change law of the CNN under RMSProp and Adam optimal controllers are compared. The image analysis results show that the Adam optimal controller can quickly find the direction, and the gradient decreases greatly. In addition, the accuracy of the recommendation system is 55.84%. Compared with the traditional CNN algorithm, this paper uses the convolutional neural network (CNN) to analyze and recommend piano music images according to users’ preferences, which can realize more accurate piano music recommendation for users in the big data environment. Therefore, the piano music recommendation system based on the CNN has strong feature learning ability and good prediction and recommendation ability.

Music Physiology, Erotic Encounters, and Queer Reading Practices in Teleny

While music often appears as a “code” for sexual desire in Victorian literature, this article explores music's presence in a text for which no veiled language was needed: the anonymously published pornographic novella Teleny (1893). The authors of Teleny invoke emerging scientific discourses about music physiology to draw explicit parallels between musical and sexual encounters—as when the protagonist Camille orgasms in response to the vibrations of his lover's piano music. In such moments, Teleny offers an insistent defense of queer desire as a natural process rooted in the organic and often involuntary actions of the muscles and nerves—a particularly powerful intervention at a time when sexual “inversion” was most often denigrated as unnatural. In its use of biological science in the service of sexual representation—science that many twenty-first-century queer theorists might deem “essentialist”—Teleny presents a compelling challenge to scholars grappling with conversations about normativity, resistance, utopian desires, and idealized cultural objects.

INTERPRETATION PECULIARITIES OF THE CAPRICE GENRE IN F. MENDELSSOHN’S PIANO CREATIVITY

Statement of the problem. The centuries-old development of the genre of piano caprice (capriccio), which led to its flourishing in the work of romantic composers, is considered as an integral part of the genre system in Western European piano music. Insufficient study of Mendelssohn’s piano works, in particular caprices, determines the relevance of the research. The purpose of the article is to generalize stylistic qualities of the composer’s piano caprices in the context of genre evolution and their performance features. Analysis of research and publications. The genre of caprice is studied in the historical research of T. Livanova (1983), who equates the form of fantasy and capriccio-ricercare. V. Protopopov (1979) reveals the connection between fantasycapriccio and fugue in the early 17th century. K. Agisheva (2007) examines the historical aspects of the study of the capriccio genre. Modern Western European researchers, analyzing the genre of piano caprice, emphasize that its musical texture is filled with elements of vocal lyrics and mood swings (Lewandowski, 2017; Keym, 2009). At the same time, the issues of performance features remain unclear. Methods. Complex methodological approach applied in the article (historical, genre, structural-functional, performаnce research methods) allows us to trace the development of caprice from the Baroque era to Romanticism and conduct an intonational-dramatic analysis of Mendelssohn’s works in accordance with the following criteria: musical form (dramaturgy), textural presentation, thematic development, tempo-rhythmic characteristics, nature of thematism. Analysis of recent research and publications. Baroque caprice is a work of polyphonic composition and improvisational construction (J. S.Bach, G.F. Handel, I. Sweelink, J. Frescobaldi). In the era of Viennese Classicism, caprice was not very popular due to its improvisational, bizarre nature, contradicting to the aesthetic ideals of the time. The genre of piano caprice became widespread in the era of Romanticism in the works of F. Mendelssohn, whose distinguished style is marked by virtuosity, melody, grace, sentimentality, clarity of presentation. Among the works of F. Mendelssohn there are seven caprices for solo piano and with orchestra. The intonational-dramatic analysis of Mendelssohn’s piano caprices makes it possible to trace the main stylistic qualities of the genre and to reveal its performance features. Conclusions. The work outlines the stylistic traits of Mendelssohn’s piano caprices ассording to such parameters: – compositional structure of his piano caprices is a one-movement composition or a cyclic one, composed of two or three movements; – texture of the music is determined by polyphonic orchestral elements and broad cantilena themes; – thematic development is based on repetition, variability or variation; – tempo-rhythm is characterized by three-beat pulsation, syncopation of rhythm, sharp accentuation; – thematicism is determined by synthesis of lyrical and decisively acting images inherent in the style of Mendelssohn. Hence, the main task for the performer is clarity, expressive intonation of the melody in combination with a “pearl” light touch and energetic dynamic tempo rhythm.