Joensuu, Finland

Machine Learning for Speech

when 17 August 2020 - 21 August 2020
language English
duration 1 week
credits 3 EC
fee EUR 300

Due to the covid-19 outbreak, all programmes for 2020 have been cancelled.

Basics of digital speech processing (1 day)
Speech as acoustic and linguistic object, representation of digital speech signal, Fourier transform, mel-frequency cepstral coefficients, linear prediction.
Basics of statistical pattern recognition and machine learning (1,5 days)
Elementary supervised and unsupervised learning, brief introduction to classic pattern recognition (Bayes’ rule, normal distribution, mixture models, logistic regression, dimensionality reduction, etc.) as well as modern deep learning models (feedforward, convolutive and recursive neural networks).
Speaker and language recognition as machine learning problem (1 day)
Representation learning for speaker and language recognition, including Gaussian mixture model supervectors, i-vector, x-vector, and back-end modeling techniques. Objective evaluation of speaker recognition, score calibration.
Research problems of speech technology (1,5 days)
Emerging research problems in speaker recognition and related problems, including spoofing attack detection, ASVspoof challenge, voice conversion, generative adversarial networks.

Course leader

Tomi Kinnunen, tkinnu(at)

Target group

Master, Doctoral

Course aim

The course is intended as a brief introduction to machine learning techniques and their application to selected speech applications. We focus in particular to speaker and language recognition and voice anti-spoofing, and will briefly touch upon other miscellaneous topics. The course will involve lectures, practicals / computer exercises, and learning diary. While no formal pre-requirements are set, sufficient programming knowledge and certain level of mathematics/statistics (linear algebra and probability theory) will be helpful for the maximum benefit of the participant. The foreseen programming tools in the 2019 course edition include Python and to a lesser extent, Matlab.

Credits info

3 EC
ECTS (+ project work 2 ECTS)

Fee info

EUR 300: Course fee. There is a discount of 20 % for the UEF partner university students.
EUR 200: Course fee for the exchange students starting in autumn 2020.


Not available.