Sixteen singers, ranging in age from 20 to 61 y, wore an MA device adhered to the sternum, just below the sternal notch. The participants sang six different vocal exercises through their full vocal range (hums, glides, legato scales, arpeggios, staccato scales, and monotones with varied dynamics) followed by a song of their choice for 4 min. The participants then read from the first chapter of the book Grit: The Power of Passion and Perseverance for 10 min (20 ). These samples served as the training set for the development of machine learning algorithms, capable of distinguishing singing from speaking with 91% accuracy.
Protocol detail
Singing vs. Speaking: Machine Learning Analysis
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Device
Singers
Sternal
Corresponding Organization :
Other organizations : Northwestern University, University of California, Davis, Massachusetts Institute of Technology, Sibel (United States), Korea Institute of Science and Technology, New York University
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Variable analysis
independent variables
- Participants' age (ranging from 20 to 61 years)
- Ability to distinguish singing from speaking with 91% accuracy
- Use of MA device adhered to the sternum, just below the sternal notch
- Participants singing six different vocal exercises through their full vocal range (hums, glides, legato scales, arpeggios, staccato scales, and monotones with varied dynamics)
- Participants reading from the first chapter of the book Grit: The Power of Passion and Perseverance for 10 minutes
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