Jeffrey J. Berry

CV
See my Github and LinkedIn pages
I am now a Research Scientist at InsideSales.com

Dissertation
- Berry, J. (2012). Machine Learning Methods for Articulatory Data. Ph.D. dissertation, University of Arizona.
Papers
- D'Ausilio, A., Maffongelli, L., Bartoli, E., Campanella, M., Ferrari, E., Berry, J. and Fadiga, L. (2014). Listening to speech recruits specific tongue motor synergies as revealed by transcranial magnetic stimulation and tissue-Doppler ultrasound imaging. Philosophical Transactions of the Royal Society B, 365(1644).
- Bartoli, E., D'Ausilio, A., Berry, J., Badino, L., Bever, T., and Fadiga, L. (2013). Listener-speaker perceived distance predicts the degree of motor contribution to speech perception. Cerebral Cortex.
- Berry, J. and Fadiga, L. (2013). Data-driven design of a sentence list for an articulatory speech corpus. Interspeech 2013, pp. 1287-1291.
- Berry, J., Fasel, I., Fadiga, L. and Archangeli, D. (2012). Training deep nets with imbalanced and unlabeled data. Interspeech 2012, pp. 1756-1759.
- Berry, J., Ji, S., Fasel, I., and Archangeli, D. (2011). Articulatory reduction in Mandarin Chinese words. Interspeech 2011, pp. 2809-2812.
- Berry, J., and Fasel, I. (2011). Dynamics of tongue gestures extracted automatically from ultrasound. International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 557-560.
- Archangeli, D., Berry, J., Ji, S., Josephs, K., Hunt, N., Fisher, M., and Carnie, A. (2011). ATR in Scottish Gaelic tense sonorants. In A. Carnie (ed.) Formal Approaches to Celtic Linguistics, pp. 283-306. Cambridge University Press.
- Fasel, I., and Berry, J. (2010). Deep belief networks for real-time extraction of tongue contours from ultrasound during speech. 20th International Conference on Pattern Recognition (ICPR), pp. 1493-1496.
Research
- Ultrasound
- Scottish Gaelic Text-to-Speech
Teaching
- LING 388, Fall 2009
Semitic Languages

Updated 2014-05-04