The Centre for Speech Technology Research, The university of Edinburgh

The ESPRESSO Project: Students

Espresso I

Alex Strachan

Alex used HMMs for feature detection and compared their performance on both SPE and multivalued feature systems for his first degree in Artificial Intelligence and Linguistics final year project.

Stefanie Aalburg

Stefanie's MSc project examined surface form variation at the syllable level. One of the aims of the Espresso project is to account for systematic variations within the syllable models themselves, allowing pronuncation dictionaries to be written in terms of lexical syllables. Statistics about the types of surface form variation will be a valuable resource. Stefanie's MSc. in Speech and Language Processing dissertation was:

Todd Stephenson

Todd' first project used neural networks to perform the same tasks as Alex's HMMs. He then used the NN output for phone recognition using HMMs. His dissertation extended this to syllable modelling. State-tied triphone models were used for phone recognition, and a similar system for syllable recognition, both employing tying driven by decision trees. He investigated various HMM topologies for syllable models. Todd is now studying for a PhD at the Institut Dalle Molle d'Intelligence Artificielle Perceptive (IDIAP) with Hervé Bourlard (email During his MSc. in Cognitive Science Todd produced:

Angela Michelfelder

Angela's MSc project investigated whether there is a "natural" segmentation of articulatory data - do the articulatory trajectories themselves suggest (bottom-up) a set of segments, and what relationship is there with a top-down definition, such as the syllable? Are syllable boundaries apparent in the articulatory data? What about phone boundaries?

Simon Ahern

Simon's MSc project investigated Government Phonology, which uses a system of around 8 primes to describe segments.

Espresso II

Joe Frankel

Joe's PhD project is investigating various aspects of linear dynamical models for ASR, including Dissertation due late 2002.

Fiona Couper

Fiona's MSc project was a pilot for Espresso III and investigated ways of enhancing the power of LDMs by introducing mutliple sets of model parameters, which are controlled by a simple finite state switching process with two parallel states (in contrast to the sequential states used by Joe above). We ultimately hope to use topologies that combine both features. The main focus of Fiona's project was how to train what is effectively a "mixture of LDMs" and she investigated three methods: Dissertation due Sept 2002.

Espresso III

Fiona Couper

Fiona's PhD will start early 2003 - watch this space!