@inproceedings{63709e7d57be4874bada8ef69bdc5713,
title = "Introducing Machine Learning in Undergraduate DSP Classes",
abstract = "Machine Learning (ML) and Artificial Intelligence (AI) algorithms are enabling several modern smart products and devices. Furthermore, several initiatives such as smart cities and autonomous vehicles utilize AI and ML computational engines. The current and emerging applications and the growing industrial interest in AI necessitate introducing ML algorithms at the undergraduate level. In this paper, we describe a series of activities to introduce ML in undergraduate digital signal processing (DSP) classes. These activities include a computational comparative study of ML algorithms for spoken digit recognition using spectral representations of speech. We choose spectral representations and features for speech as those concepts associate with the core topics in DSP such as FFT and autoregressive spectra. Our primary objective is to introduce undergraduate DSP students to feature extraction and classification using appropriate signal analysis and ML tools. An online module on ML along with a computer exercise are developed and assigned as a semester project in the DSP class. The exercise is developed in Python and also on the online JDSP HTML5 environments. An assessment study of the modules and computer exercises are also part of this effort.",
keywords = "AI, DSP education, J-DSP, Machine Learning, Online laboratory, Python, Spectrogram",
author = "Shanthamallu, {Uday S.} and Sunil Rao and Abhinav Dixit and Narayanaswamy, {Vivek S.} and Jie Fan and Andreas Spanias",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 ; Conference date: 12-05-2019 Through 17-05-2019",
year = "2019",
month = may,
doi = "10.1109/ICASSP.2019.8683780",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7655--7659",
booktitle = "2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings",
}