The University of Southampton
Telephone:
+442380596675
Email:
c.evers@soton.ac.uk

Dr Christine Evers 

Christine Evers is a Lecturer (Assistant Prof. equivalent) in Computer Science. Her research focuses on Bayesian learning for machine listening. Her research is on the intersection of robotics, machine learning, statistical signal processing, and acoustics.

Prior to joining the University of Southampton, Christine was the recipient of an EPSRC Fellowship to advance her work on "Acoustic Signal Processing and Scene Analysis for Socially Assistive Robots", hosted at Imperial College London. Her fellowship followed positions as a research associate on the FP7 project "Embodied Audition for Robots" at Imperial College between 2014-2016; as a senior systems engineer at Selex Electronic Systems, Edinburgh, between 2010-2014; and as a research fellow at the University of Edinburgh between 2009-2010. Christine received her PhD from the University of Edinburgh, UK, in 2010; her MSc degree in Signal Processing and Communications from the University of Edinburgh in 2006; and her BSc degree in Electrical Engineering and Computer Science from Jacobs University, Germany in 2005. 

Christine is a Senior Member of the IEEE, an elected member of the IEEE Signal Processing Society Technical Committee on Audio and Acoustic Signal Processing, and serves as an associate editor of the EURASIP Journal on Audio, Speech, and Music Processing.

Full publication list on Google Scholar

Research

Research interests

My research is in the area of machine listening, and equips autonomous agents with the ability to extract semantic cues from microphone signals in order to answer the questions "Where am I?", "What are the sounds around me?", and "How can I interact in my acoustic environment?". The objective of my research is to provide agents, such as robots, with situational awareness in order to reason and interact within complex, acoustic environments, affected by interference, noise, and reverberation. 

Publications

Moore, Alastair, Evers, Christine and Naylor, Patrick (2017) Direction of arrival estimation in the spherical harmonic domain using subspace pseudointensity vectors. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 25 (1), 178-192. (doi:10.1109/TASLP.2016.2613280).

Evers, Christine and Naylor, Patrick (2018) Acoustic SLAM. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26 (9), 1484 - 1498. (doi:10.1109/TASLP.2018.2828321).

Evers, Christine, Loellmann, Heinrich W., Mellmann, Heinrich, Schmidt, Alexander, Barfuss, Hendrik, Naylor, Patrick A. and Kellermann, Walter (2020) Data Corpus for the IEEE-AASP Challenge on Acoustic Source Localization and Tracking (LOCATA). Zenodo doi:10.5281/zenodo.3630471 [Dataset]

Evers, Christine, Habets, Emanuel, Gannot, Sharon and Naylor, Patrick (2018) DoA reliability for distributed acoustic tracking. IEEE Signal Processing Letters, 25 (9), 1320-1324. (doi:10.1109/LSP.2018.2849579).

Ban, Yutong, Alameda-Pineda, Xavier, Evers, Christine and Horaud, Radu (2019) Tracking multiple audio sources with the von Mises distribution and variational EM. IEEE Signal Processing Letters, 26 (6), 798-802. (doi:10.1109/LSP.2019.2908376).

Evers, Christine and Naylor, Patrick (2018) Optimized self-localization for SLAM in dynamic scenes using probability hypothesis density filters. IEEE Transactions on Signal Processing, 66 (4), 863-878. (doi:10.1109/TSP.2017.2775590).

Neo, Vincent W., Evers, Christine and Naylor, Patrick A. (2020) PEVD-Based Speech Enhancement in Reverberant Environments. In Proceedings IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.. (In Press)

Hogg, Aidan, Evers, Christine and Naylor, Patrick A. (2019) Multiple hypothesis tracking for overlapping speaker segmentation. In Proceedings IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). IEEE.. (doi:10.1109/WASPAA.2019.8937185).

Evers, Christine, Loellmann, Heinrich W., Mellmann, Heinrich, Schmidt, Alexander, Barfuss, Hendrik, Naylor, Patrick A. and Kellermann, Walter (2020) The LOCATA challenge: acoustic source localization and tracking. IEEE/ACM Transactions on Audio, Speech, and Language Processing. (doi:10.1109/TASLP.2020.2990485).

Hopgood, James R., Evers, Christine and Fortune, Steven (2010) Bayesian single channel blind dereverberation of speech from a moving talker. In, Speech Dereverberation. (Signals and Commmunication Technology, , (doi:10.1007/978-1-84996-056-4_8)) Springer, pp. 219-270. (doi:10.1007/978-1-84996-056-4_8).

Evers, Christine and Hopgood, James R. (2011) Multichannel online blind speech dereverberation with marginalization of static observation parameters in a Rao-Blackwellized particle filter. Journal of Signal Processing Systems, 63, 315-332. (doi:10.1007/s11265-009-0442-4).

Evers, Christine and Hopgood, James R. (2008) Parametric modelling for single-channel blind dereverberation of speech from a moving speaker. IET Signal Processing, 2 (2). (doi:10.1049/iet-spr:20070046).

Neo, Vincent W., Evers, Christine and Naylor, Patrick A. (2019) Speech enhancement using polynomial eigenvalue decomposition. In Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA). IEEE.. (doi:10.1109/WASPAA.2019.8937235).

Hogg, Aidan, Evers, Christine and Naylor, Patrick A. (2019) Speaker change detection using fundamental frequency with application to multi-talker segmentation. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.. (doi:10.1109/ICASSP.2019.8682924).

Evers, Christine, Loellmann, Heinrich W., Mellmann, Heinrich, Schmidt, Alexander, Barfuss, Hendrik, Naylor, Patrick A. and Kellermann, Walter (2018) Locata challenge - evaluation tasks and measures. In Proceedings of the International Workshop on Acoustic Signal Enhancement (IWAENC). IEEE.. (doi:10.1109/IWAENC.2018.8521288).

Neo, Vincent W., Evers, Christine and Naylor, Patrick A. (2020) Speech dereverberation performance of a polynomial-EVD subspace approach. European Signal Processing Conference, Netherlands. 18 - 22 Jan 2021. 5 pp . (In Press)

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