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The research aimed to develop a prototype on possible applications of such techniques in the development of musical instruments controlled by or sound generated in Max/MSP, interactive audio and/or video installations, amongst other possible developments. The main interest in using Machine Learning as a creative tool integrated with Max consisted on the set of possibilities that open up with the training possibilities facilitated by it, and how such possibilities can offer creatives working with Max/MSP new ways of interpreting and manipulating data, and as a consequence, new potential creative opportunities. | The research aimed to develop a prototype on possible applications of such techniques in the development of musical instruments controlled by or sound generated in Max/MSP, interactive audio and/or video installations, amongst other possible developments. The main interest in using Machine Learning as a creative tool integrated with Max consisted on the set of possibilities that open up with the training possibilities facilitated by it, and how such possibilities can offer creatives working with Max/MSP new ways of interpreting and manipulating data, and as a consequence, new potential creative opportunities. | ||
==Technical | ==Technical Development== | ||
===Sound=== | ===Sound=== | ||
Considering the aim of establishing a stable system between sensor, sounds synthesised on Max/MSP, its Machine Learning integration and feedback back to sound synthesis on Max (and potential Digital to Analog conversion of the same data into sensors and physical objects), the development of the sound component of the system limited itself to synthesis of sine waves. | Considering the aim of establishing a stable system between sensor, sounds synthesised on Max/MSP, its Machine Learning integration and feedback back to sound synthesis on Max (and potential Digital to Analog conversion of the same data into sensors and physical objects), the development of the sound component of the system limited itself to synthesis of sine waves. | ||
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===Sensors=== | ===Sensors=== | ||
For the prototyping of the system and its subsequent sensor integration, EMG sensors were used to capture body signal and translate it into data signal to be processed on MAX/MSP through Arduino. In the example, two sensors control the input of audio gain on two of the developed oscillators on Max/MSP, which are subsequently trained on Wekinator, and sent back to Max/MSP. | For the prototyping of the system and its subsequent sensor integration, EMG sensors were used to capture body signal and translate it into data signal to be processed on MAX/MSP through Arduino. In the example, two sensors control the input of audio gain on two of the developed oscillators on Max/MSP, which are subsequently trained on Wekinator, and sent back to Max/MSP. | ||
==Process & Method== | ==Process & Method== | ||