Page 56 - Winter2021

MACHINE LEARNING AND ACOUSTICS
Ozanich, E., Gerstoft, P., and Niu, H. (2020). A feedforward neural network for direction-of-arrival estimation. The Journal of the Acoustical Society of America 147, 2035-2048. https://doi.org/10.1121/10.0000944.
Peterson, G. E., and Barney, H. L. (1952). Control methods used in a study of the vowels. The Journal of the Acoustical Society of America 24, 175-184.
Raissi, M., Perdikaris, P., and Karniadakis, G. E. (2019). Physics- informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. Journal of Computational Physics 378, 686-707. https://doi.org/10.1016/j.jcp.2018.10.045.
Ravanelli, M., and Bengio, Y. (2018). Speaker recognition from raw waveform with SincNet. In Proceedings of 2018 IEEE Spoken Lan- guage Technology Workshop (SLT 2018), Athens, Greece, December 18-21, 2018, pp. 1021-1028.
Russell, S. J., and Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, NJ.
Sainburg, T., Thielk, M., and Gentner, T. Q. (2020). Finding, visual- izing, and quantifying latent structure across diverse animal vocal repertoires. PLoS Computational Biology 16, e1008228. https://doi.org/10.1371/journal.pcbi.1008228.
Schedl, M., Gómez, E., and Urbano, J. (2014). Music information retrieval: Recent developments and applications. Foundations and Trends in Infor- mation Retrieval 8, 127-261. https://doi.org/10.1561/1500000042.
Shah, T., Zhuo, L., Lai, P., Rosa-Moreno, A. D. L., Amirkulova, F., and Gerstoft, P. (2021). Reinforcement learning applied to metamaterial design. The Journal of the Acoustical Society of America 150, 321-338. https://doi.org/10.1121/10.0005545.
Shiu, Y., Palmer, K. J., Roch, M. A., Fleishman, E., Liu, X., Nosal, E. M., Helble, T., Cholewiak, D., Gillespie, D., and Klinck, H. (2020). Deep neural networks for automated detection of marine mammal species. Sci- entific Reports 10, 607. https://doi.org/10.1038/s41598-020-57549-y.
Stowell, D., Wood, M. D., Pamuła, H., Stylianou, Y., and Glotin, H. (2019). Automatic acoustic detection of birds through deep learning: The first Bird Audio Detection challenge. Methods in Ecology and Evolution 10, 368-380. https://doi.org/10.1111/2041-210x.13103.
van der Maaten, L., and Hinton, G. (2008). Visualizing data using t-SNE. Journal of Machine Learning Research 9, 2579-2605.
Wang, C., Wang, Z., Sun, W., and Fuhrmann, D. R. (2018). Rein- forcement learning-based adaptive transmission in time-varying underwater acoustic channels. IEEE Access 6, 2541-2558. https://doi.org/10.1109/ACCESS.2017.2784239.
Xi, S., Changsheng, X., and Kankanhalli, M. S. (2004). Unsupervised classification of music genre using hidden Markov model. In Pro- ceedings of the 2004 IEEE International Conference on Multimedia and Expo, Taipei, Taiwan, June 27-30, 2004, vol. 3, pp. 2023-2026.
Zissman, M. A. (1996). Comparison of four approaches to automatic lan- guage identification of telephone speech. IEEE Transactions on Speech and Audio Processing 4, 31. https://doi.org/10.1109/TSA.1996.481450.
Marie A. Roch received her PhD from the University of Iowa, Iowa City. Before joining San Diego State University, San Diego, California, as a professor of computer science, she was at the AT&T Bell Telephone Laboratories, Murray Hill, New Jersey, and Naperville, Illinois. Her research interests are in animal bioacoustics for conservation and mitigation, communication, and behavior. For more information, see roch.sdsu.edu.
Peter Gerstoft
pgerstoft@ucsd.edu
Scripps Institution of Oceanography University of California, San Diego 9500 Gilman Drive
La Jolla, California 92093-0238, USA
Peter Gerstoft received his PhD from the Technical University of Denmark, Kongens Lyngby, Den- mark, in 1986. Since 1997, he has been with the University of California, San Diego, La Jolla. His current research inter-
ests are signal processing and machine learning applied to acoustic, seismic, and electromagnetic signals. For more information, see noiselab.ucsd.edu. His work has been fea- tured on The Late Show with Stephen Colbert.
Bożena Kostek
bozenka@sound.eti.pg.gda.pl
Faculty of Electronics, Telecommuni- cations and Informatics
Gdansk University of Technology
ul. Narutowicza 11/12
80-233 Gdansk, Poland
Bożena Kostek is a professor at the Gdansk University of Technology, Gdansk, Poland. She is a corresponding member of the Polish Academy of Sciences and a Fellow of the Acoustical Society of America and of the Audio Engineering Society. She has published more than 600 scientific papers and has led many research projects. She is the recipient of many prestigious awards, including two first prizes from the Prime Minister of Poland, several prizes from the Minister of Science, and an award from the Polish Academy of Sciences.
Zoi-Heleni (Eliza) Michalopoulou
michalop@njit.edu
Department of Mathematical Sciences New Jersey Institute of Technology University Heights
Newark, New Jersey 07102-1982, USA
Zoi-Heleni (Eliza) Michalopoulou
received her PhD from Duke University, Durham, North Carolina. She is a professor at the New Jersey Institute of Technology, Newark. She is a Fellow of the Acousti- cal Society of America and a Senior Member of the IEEE. Her research interests include ocean acoustics, Bayesian modeling, inverse problems, array signal processing, and machine learning.
About the Authors
Marie A. Roch
marie.roch@sdsu.edu
Department of Computer Science
San Diego State University
5500 Campanile Drive
San Diego, California 92182-7720, USA
56 Acoustics Today • Winter 2021