Digital Signal Processing

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Digital Signal Processing

Students at DeKUT are currently taught digital signal processing (DSP) in the final year of their five year program. The aim of the course is to introduce the student to a number of fundamental DSP concepts including:

  1. Discrete time signals and systems
  2. Linear time invariant (LTI) systems
  3. Frequency-domain representation of discrete time systems
  4. z-transform
  5. Sampling of continuous time signals
  6. Filter design
  7. The discrete Fourier transform

Currently, the laboratory exercises in this course are Matlab based and focus on learning how to manipulate discrete signals, plot frequency responses of digital LTI systems and design digital filters. These exercises are designed to ensure the students understand the theory of DSP. 

We propose to design a Raspberry Pi based DSP laboratory which will further enhance the understanding of these concepts by exposing the students to the processing of the human voice. A large number of DSP applications deal with speech processing and are now found in modern day electronics. These include speaker identification and speech identification. We aim to introduce the students to speech processing using a simple example, the estimation of fundamental frequency in a speech segment. It is hoped that this will motivate the students to explore more advanced applications such as speech recognition.

Background