Porfírio P. Filipe

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This paper describes our research in enhance everyday devices as a solution to adapt Spoken Dialogue Systems (SDS) within ambient intelligence. In this context, a SDS enables universal access to ambient intelligence for anyone, anywhere at anytime, allowing the access to any device through any media or language. The main problem that we want to address is(More)
This paper describes the recent effort to improve our Domain Knowledge Manager (DKM) that is part of a mixed-initiative task based Spoken Dialogue System (SDS) architecture, namely to interact within an ambient intelligence scenario. Machine-learning applied to SDS dialogue management strategy design is a growing research area. Training of such strategies(More)
The goal of this research work is to introduce the concept of a lower cost flexible system for ticketing purposes implemented on a cloud platform. We propose therefore the evolution of the traditional architecture of ticketing for a cloud based architecture in which the core processes of ticketing are offered through a Software-as-a-Service (SaaS) business(More)
This paper presents a knowledge modeling approach to improve domain-independency in Spoken Dialogue Systems (SDS) architectures. We aim to support task oriented dialogue management strategies via an easy to use interface provided by an adaptive Domain Knowledge Manager (DKM). DKM is a broker that centralizes the knowledge of the domain using a Knowledge(More)