Browsing by Person "King, Simon"

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Dynamical system modelling of articulator movement
(1999) King, Simon; Wrench, Alan A.
We describe the modelling of articulatory movements using (hidden) dynamical system models trained on Electro-Magnetic Articulograph (EMA) data. These models can be used for automatic speech recognition and to give insights into articulatory behaviour. They belong to a class of continuous-state Markov models, which we believe can offer improved performance over conventional Hidden Markov Models (HMMs) by better accounting for the continuous nature of the underlying speech production process - that is, the movements of the articulators. To assess the performance of our models, a simple speech recognition task was used, on which the models show promising results.
Recording speech articulation in dialogue: Evaluating a synchronized double Electromagnetic Articulography setup
(Elsevier, 2013-08-28) Geng, Christian C.; Turk, Alice; Scobbie, James M.; Macmartin, Cedric; Hoole, Philip; Richmond, Korin; Wrench, Alan A.; Pouplier, Marianne; Bard, Ellen Gurman; Campbell, Ziggy; Dickie, Catherine; Dubourg, Eddie; Hardcastle, William J.; Kainada, Evia; King, Simon; Lickley, Robin; Nakai, Satsuki; Renals, Steve; White, Kevin; Wiegand, Ronny; EPSRC
We demonstrate the workability of an experimental facility that is geared towards the acquisition of articulatory data from a variety of speech styles common in language use, by means of two synchronized electromagnetic articulography (EMA) devices. This approach synthesizes the advantages of real dialogue settings for speech research with a detailed description of the physiological reality of speech production. We describe the facility's method for acquiring synchronized audio streams of two speakers and the system that enables communication among control room technicians, experimenters and participants. Further, we demonstrate the feasibility of the approach by evaluating problems inherent to this specific setup: The first problem is the accuracy of temporal synchronization of the two EMA machines, the second is the severity of electromagnetic interference between the two machines. Our results suggest that the synchronization method used yields an accuracy of approximately 1 ms. Electromagnetic interference was derived from the complex-valued signal amplitudes. This dependent variable was analyzed as a function of the recording status - i.e. on/off - of the interfering machine's transmitters. The intermachine distance was varied between 1 m and 8.5 m. Results suggest that a distance of approximately 6.5 m is appropriate to achieve data quality comparable to that of single speaker recordings.
The Edinburgh Speech Production Facility DoubleTalk Corpus
(International Speech Communication Association, 2013-08-25) Scobbie, James M.; Turk, Alice; Geng, Christian; King, Simon; Lickley, Robin; Richmond, Korin
The DoubleTalk articulatory corpus was collected at the Edinburgh Speech Production Facility (ESPF) using two synchronized Carstens AG500 electromagnetic articulometers. The first release of the corpus comprises orthographic transcriptions aligned at phrasal level to EMA and audio data for each of 6 mixed-dialect speaker pairs. It is available from the ESPF online archive. A variety of tasks were used to elicit a wide range of speech styles, including monologue (a modified Comma Gets a Cure and spontaneous story-telling), structured spontaneous dialogue (Map Task and Diapix), a wordlist task, a memory-recall task, and a shadowing task. In this session we will demo the corpus with various examples.