3 resultados para Other Music
em Digital Commons at Florida International University
Resumo:
iGrooving is a generative music mobile application specifically designed for runners. The application’s foundation is a step-counter that is programmed using the iPhone’s built-in accelerometer. The runner’s steps generate the tempo of the performance by mapping each step to trigger a kick-drum sound file. Additionally, different sound files are triggered at specific step counts to generate the musical performance, allowing the runner a level of compositional autonomy. The sonic elements are chosen to promote a meditative aspect of running. iGrooving is conceived as a biofeedback-stimulated musical instrument and an environment for creating generative music processes with everyday technologies, inspiring us to rethink our everyday notions of musical performance as a shared experience. Isolation, dynamic changes, and music generation are detailed to show how iGrooving facilitates novel methods for music composition, performance and audience participation.
Resumo:
The rapid growth of the Internet and the advancements of the Web technologies have made it possible for users to have access to large amounts of on-line music data, including music acoustic signals, lyrics, style/mood labels, and user-assigned tags. The progress has made music listening more fun, but has raised an issue of how to organize this data, and more generally, how computer programs can assist users in their music experience. An important subject in computer-aided music listening is music retrieval, i.e., the issue of efficiently helping users in locating the music they are looking for. Traditionally, songs were organized in a hierarchical structure such as genre->artist->album->track, to facilitate the users’ navigation. However, the intentions of the users are often hard to be captured in such a simply organized structure. The users may want to listen to music of a particular mood, style or topic; and/or any songs similar to some given music samples. This motivated us to work on user-centric music retrieval system to improve users’ satisfaction with the system. The traditional music information retrieval research was mainly concerned with classification, clustering, identification, and similarity search of acoustic data of music by way of feature extraction algorithms and machine learning techniques. More recently the music information retrieval research has focused on utilizing other types of data, such as lyrics, user-access patterns, and user-defined tags, and on targeting non-genre categories for classification, such as mood labels and styles. This dissertation focused on investigating and developing effective data mining techniques for (1) organizing and annotating music data with styles, moods and user-assigned tags; (2) performing effective analysis of music data with features from diverse information sources; and (3) recommending music songs to the users utilizing both content features and user access patterns.
Resumo:
This study examines the correlation between how certified music educators understand audio technology and how they incorporate it in their instructional methods. Participants were classroom music teachers selected from fifty middle schools in Miami- Dade Public Schools. The study adopted a non-experimental research design in which a survey was the primary tool of investigation. The findings reveal that a majority of middle school music teachers in Miami-Dade are not familiar with advanced audiorecording software or any other digital device dedicated to the recording and processing of audio signals. Moreover, they report a lack of opportunities to develop this knowledge. Younger music teachers, however, are more open to developing up-to-date instructional methodologies. Most of the participants agreed that music instruction should be a platform for preparing students for a future in the entertainment industry. A basic knowledge of music business should be delivered to students enrolled in middle-school music courses.