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Doctor Jennifer Williams

Doctor Jennifer Williams

Lecturer

Research interests

  • Dr Williams conducts research in audio processing as it is applied to smart cities and smart buildings. She investigates connections between audio AI services in smart buildings that can detect and analyse occupant presence, movement, and activity levels and incorporating this information into reinforcement learning algorithms to simultaneously optimise resource consumption (energy, ventilation, cost, etc) with occupant preferences and comforts.
  • 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 and chips via TinyML). Her work addresses ethical issues of trust for audio AI, spanning a breadth of topics such as: deepfake detection, voice as a form of property, and speaker and content privacy.

More research

Connect with Jennifer

Email: j.williams@soton.ac.uk

Address: B32, East Highfield Campus, University Road, SO17 1BJ (View in Google Maps)

About

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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