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Doctor Jennifer Williams

Dr Jennifer Williams


Research interests

  • Dr Williams conducts research in responsible and trustworthy audio processing applied to a variety of domains and use-cases. Along these lines, her research also addresses issues of audio AI safety in terms of usability, privacy, and security. These issues overlap with procesing in edge devices (e.g., ultra low-power devices). Her work addresses ethical issues of trust for audio AI, spanning a breadth of topics such as: deepfake detection, voice-related rights, and speaker and content privacy.

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Dr Jennifer Williams is a postdoctoral Research Fellow on the Citizen-Centric AI Systems project and she is PI of a UKRI TAS Agile project on trustworthy audio. Her current research explores speech/audio solutions to trustworthy and explainable smart energy management. She completed her PhD at University of Edinburgh in the area of representation learning and speech signal disentanglement applied to a variety of speech technology applications (voice conversion, speech synthesis, anti-spoofing, naturalness assessment, and privacy). Before her doctoral work, she was a staff member at MIT Lincoln Laboratory for five years where she developed rapid prototyping solutions for text and speech technology. She is a member of IEEE and ISCA, serves as a committee member of the ISCA-PECRAC group, and co-organizes ISCA SPSC-SIG events. She is a reviewer for multiple conferences involving AI, text, speech, and multimedia. She holds an MScR in Data Science from University of Edinburgh, an MS in Computational Linguistics from Georgetown University (USA), and a BA in Applied Linguistics, magna cum laude, from Portland State University (USA).

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