Matching Items (2)
- All Subjects: Audio
- Creators: Kosut, Oliver
- Creators: Thorn, Seth
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
- Status: Published
In this paper, I propose that taking an embodied approach to music performance can allow for better gestural control over the live sound produced and greater connection between the performer and their audience. I examine the many possibilities of live electronic manipulation of the voice such as those employed by past and current vocalists who specialize in live electronic sound manipulation and improvisation. Through extensive research and instrument design, I have sought to produce something that will benefit me in my performances as a vocalist and help me step out from the boundaries of traditional music performance. I will discuss the techniques used for the creation of my gestural instrument through the lens of my experiences as a performer using these tools. I believe that, through use of movement and gesture in the creation and control of sound, it is more than possible to step away from conventional ideas of live vocal performance and create something new and unique, especially through the inclusion of improvisation.
Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.