Max as a Digital Platform for Noise Music Performance - Mokhtar, Muhamad Hafifi; Chan, Clare Suet Ching (Harmonia: Journal of Arts Research and Education, 2023)
This article explores Max as a digital platform for performing noise music through a practice-led research method. The practice-led research method was used to explore the possibilities of building Max patches, while content analysis method was used to analyse the outcome of the patches. Several Max patches were created to explore the potential of Max as an alternative approach for performing noise music. Findings show that Max can replicate the audio processing methods used in conventional performance. Due to Max capabilities, some of these methods could be automated and arranged prior to the performance. In addition, Max patches featured changing sound, random pitches, mixture of pre-recorded audio source and live instrument, and drone sound combined with automatic constant real-time audio self-processing and automatic audio panning, a feature that seldom appears in the local noise music scene. In conclusion, this research argues that Max has much potential for creating a variety of digital sounds that are harsh and dissonant to the ears, therefore contributing to the musical diversity in noise music performance. These sounds are the results of the features of audio self-processing, random pitches, automatic audio panning object and self-changing pitched drone audio signals relying on random MIDI values that appeared in Max.