This paper deals with the formulation of an alternative, structural, approach to the speech representation and recognition problem. In this approach, we require both the representation and the learning algorithms to be linguistically meaningful and to naturally represent the linguistic data at hand. This allows the speech recognition system to discover the emergent combinatorial structure of the linguistic classes. The proposed approach is developed within the ETS formalism, the first formalism in applied mathematics specifically designed to address the issues of class and object/event representation. We present an initial application of ETS to the articulatory modelling of speech based on elementary physiological gestures that can be reliably represented as the ETS primitives. We discuss the advantages of this gestural approach over prevalent methods and its promising potential to mathematical modelling and representation in linguistics.
|Title of host publication||Pattern Representation and the Future of Pattern Recognition (Proc. Satellite Workshop of 17th International Conference on Pattern Recognition)|
|Number of pages||20|
|Publication status||Published - 1 Aug 2004|