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Research on Music, Voices, and Technology
MAS: Media Arts and Sciences
Rébecca Kleinberger: email@example.com
In this role you will have the opportunity to work with experts in music and technology to develop various projects and experiences. One of the projects you would contribute to is how to use musically modulated signals to alleviate stuttering. Did you know that people who stutter almost never stutter when they sing? Here at MIT Media Lab’s Opera of the Future group, we are using audio analysis tools in Python and MATLAB, musical modulation tools including PureData and Max, and machine learning techniques to leverage this interesting fact and determine what sorts of vocal modulations are most effective at remediating stutter. Stuttering is a vocal communication disorder that affects approximately 1% of the adult population worldwide, and those who have it know how difficult it can make regular social interaction. Using modulated vocal feedback (playing one’s own voice back to them with some modification), we seek to decrease the prevalence of stutter in those who struggle with it. We have seen promising results in early trials and we want to experiment further with new techniques. As a UROP in Opera of the Future, you will be part of this trailblazing research movement. You would be: - working on algorithms for stutter detection using machine learning techniques, audio modulation algorithms, and/or data analysis for our trials; - helping us design and run human studies with people who experience stuttering; - helping with data analysis; - building relevant wearable devices; - other projects that suit your skills and interests.
- A good command of Python; - Experience in Machine Vision, Natural Language Processing or DeepSpeech is a plus; - Willingness to learn new software; - Excellent interpersonal and organizational skills ; - Some knowledge of audio recording/analysis software such as Reaper and Praat would be helpful but not required. Relevant URL: rebeccakleinberger.com