The topics include:
Part 1: Includes speech signal acquisition, visualisation, pre-processing: UoA Mediastore Link
Part 2: Includes hand-crafted features and spectrogram of a speech signal: UoA Mediastore Link
Part 3: Includes speech feature analysis, towards Machine learning and evaluation: UoA Mediastore Link
Also, including the links to the analysis tools mentioned in the presentation: Praat: https://www.fon.hum.uva.nl/praat/
WavSurfer: https://sourceforge.net/projects/wavesurfer/
EmuR: https://ips-lmu.github.io/EMU.html
R Studio: https://rstudio.com/
ggplot2: https://r4ds.had.co.nz/data-visualisation.html
Librosa: https://librosa.org/doc/latest/index.html
OpenSmile: https://github.com/audeering/opensmile-python
JLCorpus: https://github.com/tli725/JL-Corpus
These resources were compiled by Dr Jesin James.