Vocal Alchemy: Shaping Voices with Signal Processing

Course Description

Brain waves, speech, and music are all phenomena that can be encoded in digital signals. On the most basic level, a digital signal is a numerical representation of a stream of data over time. Signal processing can also include multidimensional data arrays, such as videos or fMRIs (functional magnetic resonance imaging). The real power of digital signals is that they allow for flexible manipulation of these data in order to change the output (voice changing, audio processing/effects) or analyze the signal (spectral analysis, measuring loudness or noisiness, segmenting into distinct elements). Thanks to widely available computer and audio hardware combined with various software packages, it is possible to work with these techniques in real-time systems, which enable direct feedback for the user of the system. After establishing some basics of how these techniques are implemented, we will be focusing on building or reengineering our own practical systems used in medical diagnosis or linguistics, with the goal of presenting these systems as working demonstrations or interactive installations connected with an end of semester poster presentation. While we will cover theoretical concepts, this will be a hands-on course, where we will work to develop projects.

We will be using a range of software programs to implement our projects, but importantly students do not need a background in programming, math, or physics to successfully complete projects. We will take advantage of visual data flow languages that do not require a detailed knowledge of computer coding, but which still allow for us to flexibly manipulate many variables of the signal processing chain.

Taught by a team of three instructors from the areas of linguistics (Professor Dr. Kevin Tang), medicine (Professor Dr. Esther Florin), and music (Dr. Carter Williams), this course will embrace an interdisciplinary approach to digital signal processing that will allow student to explore applications in medicine, linguistic, and creative fields.

Learning outcomes:

Students will be able to:

• Explain and implement basic concepts of digital signal processing
• Articulate and apply basic concepts of brain processes (language, and multiple modal input)
• Analyze research questions from a multidisciplinary perspective

Students will acquire the following practical skills:

• Technical skills: employ a range of signal processing tools (both software and hardware)
• Soft skills: project management, problem solving, translation of a problem into practical requirements