@article { , title = {Speech synthesis parameter generation for the assistive silent speech interface MVOCA}, abstract = {In previous publications, a silent speech interface based on permanent-magnetic articulography (PMA) has been introduced and evaluated using standard automatic speech recognition techniques. However, word recognition is a task that is computationally expensive and introduces a significant time delay between speech articulation and generation of the acoustic signal. This paper investigates a direct synthesis approach where control parameters for parametric speech synthesis are generated directly from the sensor data of the silent speech interface, without an intermediate lexical representation. Users of such a device would not be tied to the limited vocabulary of a word-based recogniser and could therefore express themselves more freely. This paper presents a feasibility study that investigates whether it is possible to infer speech synthesis parameters from PMA sensor data}, conference = {Interspeech 2011: 12th Annual Conference of the International Speech Communication Association}, journal = {Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH}, note = {Article has no doi. Batch 008. Output ID 43580.}, pages = {3009 - 3012}, publicationstatus = {Published}, url = {https://hull-repository.worktribe.com/output/417603}, keyword = {Specialist Research - Other, Health and Health Inequalities}, year = {2011}, author = {Hofe, Robin and Ell, Stephen R. and Fagan, Michael J. and Gilbert, James M. and Green, Phil D. and Moore, Roger K. and Rybchenko, Sergey I.} }