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Memorization-Based Training and Testing Paradigm for Robust Vocal Identity Recognition in Expressive Speech Using Event-Related Potentials Analysis
Published on: August 9, 2024
Reclaiming Voice with AI
Fatima N Mirza1, Alexis Bogan2, Andrew L Beam3,4
1Department of Dermatology, Brown University Health, Providence, RI.
Abstract:
AbstractVoice impairments affect millions of Americans, with personalized text-to-speech technology offering limited solutions due to the need for extensive voice banking. Here, we report the case of Alexis Bogan, a 20-year-old patient who acutely lost her voice after surgery to resect her brain stem hemangioblastoma. In a world-first application, OpenAI's Voice Engine was used to clone Ms. Bogan's voice from just 15 seconds of preexisting audio, sourced from a school project she had filmed a few years prior. This enabled her to use a personalized text-to-speech app for daily communication while rehabilitating her speech. This case was highlighted on a recent episode of the NEJM AI Grand Rounds podcast,1 framing a broader discussion on voice cloning technology. While AI is often dual use and concerns about voice cloning often center on potential misuse, such as "deepfakes" and misinformation, we argue that suppressing this technology may inflict tangible harm on patients by denying them the chance to reclaim their voice. Inspired by Ms. Bogan's journey, we urge researchers, clinicians, ethicists, policymakers, and tech companies to collaborate swiftly yet responsibly in advancing AI voice cloning in health care. By doing so, we can empower patients to recover not just their voice, but also a fundamental aspect of their identity and quality of life.
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