Early Computer Music (1950–69)

2020 ◽  
pp. 389-405
Author(s):  
Thom Holmes
2017 ◽  
Vol 22 (2) ◽  
pp. 286-296 ◽  
Author(s):  
Giuditta Parolini

In the early days of music technologies the collaboration between musicians, scientists, technicians and equipment producers was very close. How did this collaboration develop? Why did scientific, business, and musical agendas converge towards a common goal? Was there a mutual exchange of skills and expertise? To answer these questions this article will consider a case study in early computer music. It will examine the career of the Italian cellist and composer Pietro Grossi (1917–2002), who explored computer music with the support of mainframe manufacturers, industrial R&D, and scientific institutions. During the 1970s, Grossi became an eager programmer and achieved a first-hand experience of computer music, writing several software packages. Grossi was interested in avant-garde music as an opportunity to make ‘music without musicians’. He aimed at a music composed and performed by machines, and eventually, he achieved this result with his music software. However, to accomplish it, Grossi could not be a lonely pioneer; he had to become a member, albeit an atypical one, of the Italian computing community of the time. Grossi’s story, thus, can tell us much about the collaborative efforts stimulated by the use of early computer technologies in sound research, and how these efforts developed at the intersection of science, art and industry.


2017 ◽  
Vol 22 (2) ◽  
pp. 297-307 ◽  
Author(s):  
Paul Doornbusch

This article documents the early experiments in both Australia and England to make a computer play music. The experiments in England with the Ferranti Mark 1 and the Pilot ACE (practically undocumented at the writing of this article) and those in Australia with CSIRAC (Council for Scientific and Industrial Research Automatic Computer) are the oldest known examples of using a computer to play music. Significantly, they occurred some six years before the experiments at Bell Labs in the USA. Furthermore, the computers played music in real time. These developments were important, and despite not directly leading to later highly significant developments such as those at Bell Labs under the direction of Max Mathews, these forward-thinking developments in England and Australia show a history of computing machines being used musically since the earliest development of those machines.1


2014 ◽  
Author(s):  
Florencia Garcia-Vicente ◽  
Daniel D. Garcia-Swartz ◽  
Martin Campbell-Kelly

2020 ◽  
Vol 16 (4) ◽  
pp. 15-29
Author(s):  
Jayalakshmi D. ◽  
Dheeba J.

The incidence of skin cancer has been increasing in recent years and it can become dangerous if not detected early. Computer-aided diagnosis systems can help the dermatologists in assisting with skin cancer detection by examining the features more critically. In this article, a detailed review of pre-processing and segmentation methods is done on skin lesion images by investigating existing and prevalent segmentation methods for the diagnosis of skin cancer. The pre-processing stage is divided into two phases, in the first phase, a median filter is used to remove the artifact; and in the second phase, an improved K-means clustering with outlier removal (KMOR) algorithm is suggested. The proposed method was tested in a publicly available Danderm database. The improved cluster-based algorithm gives an accuracy of 92.8% with a sensitivity of 93% and specificity of 90% with an AUC value of 0.90435. From the experimental results, it is evident that the clustering algorithm has performed well in detecting the border of the lesion and is suitable for pre-processing dermoscopic images.


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