Dogac Basaran is a post-doctoral researcher at CNRS, the French national scientific research centre. Today, in part 1 of 2, Dogac gives us a crash course in signal processing, where we learn what signal processing is and discover some of its many applications. 

Leveraging his teaching experience, Dogac uses simple language and real-world examples to explain the fundamental signal processing concepts that are used in voice technology today. He defines frequency, period, and stability, and describes how sound cards use sampling and the Nyquist theorem to convert analogue signals into digital.

He then recommends some good educational resources and software packages, so you can learn more about signal processing and get started right away on your own programming projects.

Correction [21/08/2018]: The term 'stationarity' was cited in the episode, but this should have been 'stability'.

Links from the show:

• Dogac Basaran on Github: https://github.com/dogacbasaran
• Dogac Basaran's websites: https://dbasaran.wp.imt.fr/ and http://dogacbasaran.com/
• Signal Processing MOOC on Coursera: https://www.coursera.org/learn/dsp 
• MATLAB: https://matlab.mathworks.com/
• Python Scipy STFT package: https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.stft.html 
• Humming databases: Jang, ThinkIT, IOSCAS and Task2
• ISMIR association: http://www.ismir.net/
• ISMIR 2018 conference: http://ismir2018.ircam.fr/
• CNRS: http://www.cnrs.fr/
• IRCAM: https://www.ircam.fr/

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