Dr Catherine Inez Watson

Associate Professor

In: Department of Electrical, Computer and Software Engineering » Faculty of Engineering

Biography

I joined the Department of Electrical and Computing Engineering at The University of Auckland in February 2004. Before that I had been at Macquarie University, Sydney, Australia for 8 years.

Macquarie University has a very strong tradition in speech and language research, this is spread across several departments. I had a joint position with the Department of Electronics and the Macquarie Centre of Cognitive Science. I was also a member of the Centre of Language Technology and the Speech Hearing Language Research Centre (SHLRC). I did my undergraduate degree and PhD at the University of Canterbury.

My main research interest is speech production for both humans and machines. My research includes building models of speech articulators, speech synthesis, robot speech, and acoustic phonetics.

Qualifications

Doctor of Philosophy in Electrical and Electronic Engineering, University of Canterbury, New Zealand. (1995)
Bachelor of Engineering (Hons) in Electrical and Electronic Engineering, University of Canterbury, New Zealand (1987)

Administration

Software Engineering Program Director

Academic Lab Coordinator for Forensics and Biometrics

Teaching | Current

ELECTENG 736 Analog and Digital Filter Synthesis
ELECTENG 724 Special Topic ( on Speech processing and Biometics)
SOFTENG 206 Software Engineering Design 1
SOFTENG 364 Computer Networks

Postgraduate supervision

Ben Dom, I. “Classification of emotions from glottal pulse derived from inverse filtering of the speech signal” ME (Current)

Stephen Bier “Simulating the effects of aging on the Larynx using acoustic and physiological models” PhD (Current)

Hamed Altari “Phonetics and phonology of gutturals and emphatics in Yemeni Arabic” PhD Current,Co Supervisor

Tian Li “Expressive New Zealand English Recognition Based on the Combination of Excitation Source and Vocal Tract Features” PhD Current

Jesin James “Modelling prosodic features for Empathetic Speech of a Healthcare Robot”

Hui, J “Speech enhancement for synthetic voices on a Healthcare robot for the elderly” ME 2016

Del Prado, F “Design and implementation of speech enchancement for building synthetic voices” ME, Joint Supervisor 2016

Jain, S. “Implementation of rapid voice prototyping for a Healthcare robot.” ME First Class Honours 2015

Thompson, L. “Eliciting And Analysing Perceptions Of Prosodic Prominence A Māori Case Study” PhD University of Auckland 2015

Teutenberg, J. “On the transformation of Accent” PhD, Joint Supervisor, University of Auckland 2010

Fan, H “Modelling Vocal Tracts from MRI data: Tools and Analysis” ME 2013

Liu,W “Assessing and Improving the Intelligibility of synthetic voices on a healthcare robot” ME First Class Honours 2013

Aleksandar Igic “Synthetic Speech for a Healthcare Robot: Investigation, Issues, and Implementation.” ME 2010

Onaka, A. “Articulatory and Acoustic features of Japanese Intonation” PhD (Joint Supervisor), Macquarie University, 2007

Evans, Z. “Acoustic and articulatory consequences of hypo- and hyper articulation” PhD (Co-Supervisor) Macquarie University, 2004

Areas of expertise

Speech Processing, Acoustic Phonetics, Speech Synthesis, Speech Production, Phonetics of New Zealand English and Mäori

Committees/Professional groups/Services

Professional Affiliations

President of the Australasian Speech Science and Technology Association
Partner of the New Zealand Institute of Language, Brain and Behaviour, University of Canterbury

Selected publications and creative works (Research Outputs)

Hui, C. T. J., Jain, S., & Watson, C. (2019). Effects of sentence structure and word complexity on intelligibility in machine-to-human communications. COMPUTER SPEECH AND LANGUAGE, 58, 203-215. 10.1016/j.csl.2019.03.002
James, J., Tian, L., & Watson, C. I. (2018). An Open Source Emotional Speech Corpus for Human Robot Interaction Applications. Paper presented at 19th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2018), Hyderabad, INDIA. 2 August - 6 September 2018. 19TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2018), VOLS 1-6. (pp. 5). 10.21437/Interspeech.2018-1349
Other University of Auckland co-authors: Jesin James
Mixdorff, H., Watson, C., & Keegan, P. (2018). Quantitative analysis of māori prosody from three generations. Proceedings of the International Conference on Speech Prosody. 10.21437/SpeechProsody.2018-128
URL: http://hdl.handle.net/2292/43628
Other University of Auckland co-authors: Peter Keegan
Watson, C. I., Keegan, P. J., Maclagan, M. A., Harlow, R., & King, J. (2017). The motivation and development of MPAi, a Māori Pronunciation Aid. Proceedings of Interspeech 2017, 2063-2067. Stockholm, Sweden: International Speech Communication Association. 10.21437/Interspeech.2017-215
URL: http://hdl.handle.net/2292/35553
Other University of Auckland co-authors: Peter Keegan
Maclagan, M., Watson, C. I., Harlow, R., King, J., & Keegan, P. (2017). Investigating the sound change in the New Zealand English nurse vowel. Australian Journal of Linguistics, 37 (4), 465-485. 10.1080/07268602.2017.1364126
URL: http://hdl.handle.net/2292/40134
Other University of Auckland co-authors: Peter Keegan
Bier, S. D., Watson, C. I., & McCann, C. M. (2017). Dynamic measures of voice stability in young and old adults. Logopedics Phoniatrics Vocology, 42 (2), 51-61. 10.3109/14015439.2016.1156155
URL: http://hdl.handle.net/2292/40506
Other University of Auckland co-authors: Clare McCann
Watson, C., Maclagan, M. A., King, J., Harlow, R., & Keegan, P. J. (2016). Sound change in Māori and the Influence of New Zealand English. Journal of the International Phonetics Association, 46 (2), 185-218. 10.1017/S0025100316000025
URL: http://hdl.handle.net/2292/30189
Other University of Auckland co-authors: Peter Keegan
Burgess, H., Kelly, A., & Watson, C. I. (2016). The Māori Speech Phonemes Audiogram of Familiar Sounds. New Zealand Audiological Society Bulletin, 26 (1), 14-14. Related URL.