Comparison for Improvements of Singing Voice Detection System Based on Vocal Separation

Singing voice detection is the task to identify the frames which contain the singer vocal or not. It has been one of the main components in music information retrieval (MIR), which can be applicable to melody extraction, artist recognition, and music discovery in popular music. Although there are several methods which have been proposed, a more robust and more complete system is desired to improve the detection performance. In this paper, our motivation is to provide an extensive comparison in different stages of singing voice detection. Based on the analysis a novel method was proposed to build a more efficiently singing voice detection system. In the proposed system, there are main three parts. The first is a pre-process of singing voice separation to extract the vocal without the music. The improvements of several singing voice separation methods were compared to decide the best one which is integrated to singing voice detection system. And the second is a deep neural network based classifier to identify the given frames. Different deep models for classification were also compared. The last one is a post-process to filter out the anomaly frame on the prediction result of the classifier. The median filter and Hidden Markov Model (HMM) based filter as the post process were compared. Through the step by step module extension, the different methods were compared and analyzed. Finally, classification performance on two public datasets indicates that the proposed approach which based on the Long-term Recurrent Convolutional Networks (LRCN) model is a promising alternative.Comment: 15 page

From heuristics-based to data-driven audio melody extraction

The identification of the melody from a music recording is a relatively easy task for humans, but very challenging for computational systems. This task is known as "audio melody extraction", more formally defined as the automatic estimation of the pitch sequence of the melody directly from the audio signal of a polyphonic music recording. This thesis investigates the benefits of exploiting knowledge automatically derived from data for audio melody extraction, by combining digital signal processing and machine learning methods. We extend the scope of melody extraction research by working with a varied dataset and multiple definitions of melody. We first present an overview of the state of the art, and perform an evaluation focused on a novel symphonic music dataset. We then propose melody extraction methods based on a source-filter model and pitch contour characterisation and evaluate them on a wide range of music genres. Finally, we explore novel timbre, tonal and spatial features for contour characterisation, and propose a method for estimating multiple melodic lines. The combination of supervised and unsupervised approaches leads to advancements on melody extraction and shows a promising path for future research and applications

FREEDOM AND CONSTRUCTION: NEW CONCEPTS OF FORM IN THE IMPROVISATIONS AND COMPOSITIONS OF KING CRIMSON

This thesis constructs a coherent system of analysis for the improvised and non-improvised music of the progressive rock band King Crimson, with the intention that the methodologies presented here for discussing collective improvisation should be applied to the music of other rock, jazz, and avant-garde groups. Borrowing methodology from the study of free and postmodern jazz, the thesis develops an analytical system that combines the use of intensity graphs (as developed by John Litweiler and Ingrid Monson) with traditional transcriptions and prose explanations. The intensity graphs are more complex than those created by Monson and Litweiler, as they chart the intensity of multiple instruments that are improvising simultaneously. The thesis compares the results of the intensity-graph analyses of King Crimson's improvisations with more conventional study of their pre-composed material dating from the years 1969-1974. Over the course of these five years, King Crimson's recordings reveal a growing understanding of the relationship between improvisation and composition, a significant emphasis on rhythm as a unifying factor in both composed and improvised music, and the development of several identifiable post-tonal harmonic styles (associated, respectively, with different members of the band). The recordings also expose the contributions of the band's various short-term members, most notably pianist Keith Tippett and percussionist Jamie Muir. The analyses in chapters VI and VII clearly link the harmonic language of King Crimson's compositions and that of their improvisations. They also reveal the presence of a leading instrument in most of the band's improvised pieces; as well as demonstrating that most such pieces can be analyzed as a struggle or negotiation between the players, beginning in apparent discord and ending with agreement upon a particular key and tempo. The final chapter then establishes the broad viability of the analytical method by applying it to the music of Sonic Youth, a more recent group from a considerably different musical tradition than King Crimson

A Functional Taxonomy of Music Generation Systems

Digital advances have transformed the face of automatic music generation since its beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the musical tasks targeted by different machines and the degree to which they succeed remain open questions. We present a functional taxonomy for music generation systems with reference to existing systems. The taxonomy organizes systems according to the purposes for which they were designed. It also reveals the inter-relatedness amongst the systems. This design-centered approach contrasts with predominant methods-based surveys and facilitates the identification of grand challenges to set the stage for new breakthroughs.Comment: survey, music generation, taxonomy, functional survey, survey, automatic composition, algorithmic compositio

Understanding Music: Past and Present

Understanding Music: Past and Present is an open Music Appreciation textbook co-authored by music faculty across Georgia. The text covers the fundamentals of music and the physics of sound, an exploration of music from the Middle Ages to the present day, and a final chapter on popular music in the United States. Accessible files with optical character recognition (OCR) and auto-tagging provided by the Center for Inclusive Design and Innovation.https://oer.galileo.usg.edu/arts-textbooks/1000/thumbnail.jp

Organ literature of twentieth-century black composers : an annotated bibliography

The purpose of this document is twofold: (1) to provide a comprehensive and available source of organ music by black composers and, (2) to acknowledge the composers and their compositions. A substantial amount of existing organ music by black composers is being overlooked mainly because of the lack of knowledge of its existence. The existence of a bibliography of this music would draw attention to the many works that are available and increase public awareness of lesser known composers. A bibliography of organ music by black composers does not exist. This author has addressed the problem by compiling an annotated bibliography which includes the following: (1) the identification of as many composers as possible, (2) a brief biography of each composer, (3) a complete listing of each composer's works, whether published or in manuscript, and (5) comments pertinent to the music