| Page 16 | Electronics and Computer Science

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Silicon Nano-Electro-Mechanical (NEM) and quantum devices for information processing

Dr Jennifer Williams is a postdoctoral Research Fellow on the Citizen-Centric AI Systems project. Her current research explores speech/audio solutions to trustworthy and explainable smart energy management. She completed her PhD at University of Edinburgh (2021) in the area of representation learning and speech signal disentanglement for 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 (2018), an MS in Computational Linguistics from Georgetown University (2012) and a BA in Applied Linguistics, magna cum laude, from Portland State University (2009).

Research

Research interests

* Smart cities: low-carbon comfort, energy/resource management (rooms/buildings), energy forecasting and summarization

* Audio analysis: room occupancy detection, person activity detection, audio scene understanding, localization

* Privacy: concealing speaker attributes and spoken content

* Ethics: deepfake detection, human/AI perception of deepfakes, attacker signatures, voice ownership

* Speech synthesis: multilingual / code-switched speech, voice conversion, speech disentanglement

* Voice biometrics: speaker verification

* Edge devices: TinyML on ultra-low power devices and chips

Teaching

Speech Signal Processing

Machine Learning / Deep Learning

Natural Language Processing

Ethics and Controversies in Speech / NLP

Publications

Williams, Jennifer, Comanescu, Ramona, Radu, Oana and Tian, Leimin (2018) DNN Multimodal Fusion Techniques for Predicting Video Sentiment. ACL 2018: 56th Annual Meeting of the Association for Computational Linguistics, Melbourne Convention and Exhibition Centre, Melbourne, Australia. 15 Jul 2018 - 20 Jul 2020 . 64–72 .

Müller, Nicolas M., Dieckmann, Franziska, Czempin, Pavel, Canals, Roman, Böttinger, Konstantin and Williams, Jennifer (2021) Speech is silver, silence is golden: What do ASVspoof-trained models really learn? ASVspoof 2021 Workshop: An official Interspeech 2021 satellite event,, Online. 16 Sep 2021.

Williams, Jennifer (2021) End-to-End Signal Factorization for Speech: Identity, Content, and Style. IJCAI'20 : Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, Yokohama, Yokohama, Japan. 11 - 17 Jul 2020. pp. 5212-5213 .

Gallegos, Pilar Oplustil, Williams, Jennifer, Rownicka, Joanna and King, Simon (2020) An unsupervised method to select a speaker subset from large multi-speaker speech synthesis datasets. Proceedings of the Annual Conference of the International Speech Communication Association: INTERSPEECH 2020, Shanghai, Shanghai, China. 25 Oct 2020 - 29 Oct 2022 . 1758 pp .

Williams, Jennifer, Fong, Jason, Cooper, Erica and Yamagishi, Junichi (2021) Exploring Disentanglement with Multilingual and Monolingual VQ-VAE. 11th ISCA Speech Synthesis Workshop, , Budapest, Hungary. 26 - 28 Aug 2021.

Zhao, Yi, Li, Haoyu, Lai, Cheng-I, Williams, Jennifer, Cooper, Erica and Yamagishi, Junichi (2020) Improved prosody from Learned F0 Codebook representations for VQ-VAE speech waveform reconstruction. Proceedings of the Annual Conference of the International Speech Communication Association: INTERSPEECH 2020, Shanghai, Shanghai, China. 25 Oct 2020 - 29 Oct 2022 . pp. 4417-4421 .

Williams, Jennifer and King, Simon (2019) Disentangling style factors from speaker representations. Interspeech 2019, , Graz, Austria. 15 - 19 Sep 2019. pp. 3945-3949 .

Williams, Jennifer and Rownicka, Joanna (2019) Speech replay detection with x-Vector Attack Embeddings and spectral features. Interspeech 2019, , Graz, Austria. 15 - 19 Sep 2019. pp. 1053-1057 . (doi:10.21437/Interspeech.2019-1760).

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Williams, Jennifer, Lellouch, Benjamin, Stein, Sebastian, Vanderwel, Christina and Gauthier, Stephanie (2022) Low-carbon comfort management for smart buildings. IEEE Smart Cities. 26 - 29 Sep 2022.

Published: 17 February 2022

Dr Mahmoud Wagih is one of nine researchers who were recently named as UK Intelligence Community (UKIC) Postdoctoral Research Fellows. The Fellows are being funded to develop new technologies in a range of areas including detecting and protecting against malicious drones, investigating the movement of pollutants in indoor spaces and improving radar imaging.

Mahmoud will focus his Fellowship on enabling a single energy-harvesting source to power many co-located 'satellite' systems in inaccessible environments through safe, robust and efficient radio frequency power transmission.

He said: "Harvesting energy from sunlight or vibrations could lead to battery-free electronics, yet it can only generate sufficient output where ambient power is present. Finding alternatives for replaceable batteries is crucial to improving the user's experience as our personal electronic devices increase in numbers. While we have energy harvesting devices ranging from solar-powered calculators to watches relying on body temperature to generate power, energy harvesting is yet to become a technology that works anywhere.

"I am honoured that this UKIC and the Royal Academy of Engineering award recognises our world-leading research which integrates radio frequency (RF) power harvesters in everyday objects like clothing, smart labels, and packaging. RF radiation can be used to carry power, safely, and over long ranges to inaccessible locations where sunlight or vibrations may not be present - a green alternative to batteries."

Mahmoud is working alongside industrial partners including the semiconductor leader Arm, to create new RF-powered computers, as well as Perpetuum, part of Hitachi, to build sustainable condition monitoring systems.

The UK Intelligence Community Postdoctoral Research Fellowships are offered by the Government Office for Science and are administered by the Royal Academy of Engineering. Recipients receive funding for at least two years of their project and mentorship from a Fellow of the Academy as well as an advisor from the intelligence community. They aim to provide a vital link between academia and the intelligence community and support cutting-edge work that can assist the intelligence community and also provide mentoring support to a new generation of engineers.

Mahmoud has received just under £200,000 funding for his Fellowship. Watch a video about his research here.

Fellow Southampton Research Fellow Dr Desmond Lim, from the School of Engineering, has also been awarded a UK Intelligence Community Postdoctoral Research Fellowship to lead an experimental investigation focusing on the fundamental processes in indoor airflows and the eddy diffusivity of pollutants. He has received just under £200,000 to improve numerical and mathematical models that can accurately predict the dispersions of air pollutants, improving building ventilation designs, occupants' health, and better informing government agencies responsible for public health and national defence policies.

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Publications

Hayward, Nick, Shaban, Mahdi, Badger, James, Jones, Isobel, Wei, Yang, Spencer, Daniel, Isichei, Stefania, Knight, Martin, Otto, James, Rayat, Gurinder, Levett, Denny, Grocott, Michael, Akerman, Harry and White, Neil (2022) A capaciflector provides continuous and accurate respiratory rate monitoring for patients at rest and during exercise. Journal of Clinical Monitoring and Computing. (doi:10.1007/s10877-021-00798-7).

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Research

Research interests

Teaching

Publications

Articles that may also interest you

Ingenium Biometric Laboratories and University of Southampton announce strategic collaboration in biometric technology research

New Year Honours for ECS student and visiting ECS Professor

How are Responsible AI UK connecting the AI ecosystem both nationally and internationally?

Contact

Publications

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