A Spiking Machine for Human-Computer Interactions (Design methodology)

The STANNs (Spatio-Temporal Artificial Neural Networks) are spiking neural networks. Coming from a bio-inspired data coding, they are adapted to process spatio-temporal patterns. Their capabilities have been studied for several years in the field of the natural HCIs (Human-Computer Interactions): handwritten character recognition, lipreading and speech recognition. Whereas one can observes a renewed interest for this field with the success of mobile telephony and the development of the personal digital assistants, this paper describes how to build a spiking machine with such models with an aim of integrating them in a human-software interface. The approach is illustrated by an industrial application, carried out within the framework of a collaboration between Supélec and France Telecom R&D. During this study a detailed attention was given to the evaluation of the ease of integration of this technique in a traditional procedure of software development.