Post-Doctoral Researcher

Post-doctoral research position:

Extremely-low-resource radio browsing for humanitarian monitoring

Stellenbosch University, South Africa

A post-doctoral research position focussing on the automatic identification of spoken keywords in multilingual environments with extremely few or even no resources using state-of-the-art architectures is available in the Digital Signal Processing Group of the Department of Electrical and Electronic Engineering at the University of Stellenbosch. This is part of an ongoing project to develop wordspotters that can be used to monitor community radio broadcasts in rural African regions as a source of early warning information during natural disasters, disease outbreaks, or other crises. This phase of the project will consider languages spoken in Mali, at least some of which are severely under-resourced and have not been the subject of speech technology research before. Specific project objectives include the development of research systems, the development of deployable systems, the development of new methods and techniques and the production of associated publishable outputs.

The position is part of a collaborative project with the United Nations Global Pulse. References to papers already produced as part of the project are listed below, and some general further information is available at http://pulselabkampala.ug/.

Applicants must hold a PhD (obtained within the last 5 years) in the field of Electronic/Electrical Engineering, Information Engineering, or Computer Science, or other relevant disciplines. Suitable candidates must have practical experience with automatic speech recognition systems in general and deep neural net architectures in particular, and should have an excellent background in statistical modelling and machine learning. The candidate must also have good programming skills and be able to use high level programming languages for developing prototype systems. Finally, candidates must have excellent English writing skills and have an explicit interest in scientific research and publication.

The position will be available for one year, with a possible extension to a second year, depending on progress and available funds.

Applications should include:

• A covering letter explaining why the applicant is interested in the position and what his or her most relevant qualifications are.
• A curriculum vitae that includes a list of publications and describes research projects and conference participation.
• The details of three contactable referees.

Applications should be sent as soon as possible by email to Prof Thomas Niesler (trn@sun.ac.za). The successful applicant will be subject to University policies and procedures.

Interested applicants are welcome to contact me at the above e-mail address for further information regarding the project.

References:

1. van der Westhuizen, E; Kamper, H; Menon, R; Quinn, J; Niesler, T.R. Feature learning for efficient ASR-free keyword spotting in low-resource languages. Computer Speech and Language, vol 71, pp. 101275, doi:10.1016/j.csl.2021.101275, 2022.
2. van der Westhuizen, E; Padhi, T; Niesler, T.R. Multilingual training set selection for ASR in under-resourced Malian languages. Proceedings of the 23rd International Conference on Speech and Computer (SPECOM), St Petersburg, Russia, 2021. [Virtual conference – COVID19].
3. Menon, R; Kamper, H; van der Westhuizen, E; Quinn, J; Niesler, T.R. Feature exploration for almost zero-resource ASR-free keyword spotting using a multilingual bottleneck extractor and correspondence autoencoders. Proceedings of Intespeech, Graz, Austria, September 2019.
4. Biswas, A; Menon, R; van der Westhuizen, E; Niesler, T.R. Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training. Proceedings of Intespeech, Graz, Austria, September 2019.
5. Menon, R; Biswas, A; Saeb, A; Quinn, J; Niesler, T.R. Automatic Speech Recognition for Humanitarian Applications in Somali. Proceedings of SLTU, Gurugram, India, August 2018.
6. Menon, R; Kamper, H; Yilmaz, E; Quinn, J; Niesler, T.R. ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages.. Proceedings of SLTU, Gurugram, India, August 2018.
7. Menon, R; Kamper, H; Quinn, J; Niesler, T.R. Fast ASR-free and almost zero-resource keyword spotting using DTW and CNNs for humanitarian monitoring. Proceedings of Interspeech, Hyderabad, India, September 2018.
8. Saeb, A; Menon, R; Cameron, H; Kibira, W; Quinn, J; Niesler, T.R. Very low resource radio browsing for agile developmental and humanitarian monitoring. Proceedings of Interspeech, Stockholm, Sweden, August 2017.
9. Menon, R; Saeb, A; Cameron, H; Kibira, W; Quinn, J; Niesler, T.R. Radio-browsing for Developmental Monitoring in Uganda. Proceedings of the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, USA, March 2017.