When it comes to harmonizing a group of musicians, a non-verbal way of communication must be developed to ensure that everyone is on the right pitch. So the Solfege hand signs were developed as a means to provide non-verbal communication for musicians. However, these signs pose a limitation to musicians who are visually impaired since they cannot see these hand signs. This creates a barrier for them to participate in group singing activities or practise sight singing independently.
With PitchMotion, it is possible to predict Solfege pitch gestures with the help of the acceleration data with machine learning applied to make a prediction. For the feedback system, this prototype uses both audio and visual feedback to convey which pitch the hand sign refers to, and based on the LED pattern or buzzer pitch, the user can interpret which pitch they are currently performing.
A Linear Support Vector Machine (LSVM) is a machine learning algorithm that seeks to find a linear boundary between various training set data fed by the accelerometer, aiding in the accurate prediction and classification of new data points.
Luke Goh
2023 Design Elective, TUE (Intelligent Interactive Products)
2023 Design Elective, TUE (Intelligent Interactive Products)
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