Using Praat, we synthesise a simple vowel-like sound, starting with a pulse train, which we pass through a filter with resonant peaks.
Continue reading... February 1, 2015
Autocorrelation for estimating F0
Most methods for estimating F0 start from autocorrelation. The idea is pretty simple: we are just looking for a repeating pattern in the waveform, which corresponds to the periodic vocal fold activity. For some waveforms, it might be possible to do that directly in the time domain, but in general that doesn’t work very well. […]
Continue reading... February 6, 2012
My inaugural lecture
I talk about how speech synthesis works, in what I hope is a non-technical and accessible way, and finish off with an application of speech synthesis that gives personalised voices to people who are losing the ability to speak. I also try to mention bicycles as many times as possible. For a more up-to-date, slightly more technical, […]
Continue reading... October 11, 2014
Sampling and quantisation
Is digital better than analogue? Here we discover that there are limitations when storing waveforms digitally. We learn that the consequence of sampling at a fixed rate is an upper limit on the frequencies that can be represented, called the Nyquist frequency. In addition to the limitations of sampling, storing each sample of the waveform as a […]
Continue reading... July 9, 2024
CUI 2024 video available
The video and slides from Simon’s keynote are now online under Courses > One-off events.
Continue reading... October 11, 2014
Classification and regression trees (CART)
A quick introduction to a very simple but widely-applicable model that can perform classification (predicting a discrete label) or regression (predicting a continuous value). The tree is learned from labelled data, using supervised learning. Before watching this video, you might want to check that you understand what Entropy is.
Continue reading... October 25, 2014
A super-simple speech recogniser
We make what is possibly the world’s simplest speech recognition system. It can only recognise two different words, but will help you understand the basic idea of pattern recognition using template matching. The templates are just pre-recorded words, with known labels. The features extracted are just two formant frequencies in the middle of the word, […]
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This is the new version. Still under construction.