User Interface Service Software Developerís Guide - Hitech Projects

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January 2008 Public Figure below presents the user interface of the Gesture simulator. Instead of using specific control HW random gesture events are generated by button (Send GST Event) in simulator UI. Amigo IST-2004-004182 67/114
January 2008 Public 3 Multi-modal Interface Services / Multi-device and Dialog Management Service 3.1 Component Overview 3.1.1 Voice Service 3.1.1.1 Implicit Speech Input Provider INRIA Introduction In the first part of the project, the aim of this task was to design a generic architecture to help application developers to exploit users’ implicit speech input. In the second phase of the project, the objective of this task has been to focus on one particular type of implicit speech information, and to provide it to Amigo application developers. Two kinds of implicit speech information have been first considered: automatic dialog act recognition, and topic recognition. After some research work on both aspects, INRIA has decided to choose and develop automatic topic recognition in the Amigo project, while dialog act recognition will be studied mainly as paperwork and will not be implemented in the context of Amigo. Automatic topic recognition is a particular kind of implicit speech interaction, because it transparently – without disturbing the user – exploits user’s speech. More precisely, it is implicit, because the user’s speech is not originally intended to communicate with the system, but rather to communicate with another human. Typically, the automatic topic recognition functionality might infer the current topic of discussion from two people talking together faceto-face, or from two people talking on the phone. One of the main requirements of topic recognition is its low memory and computational requirements: indeed, such an implicit system is designed to run everywhere, permanently and for many – if not all – users. This is hardly achievable when it requires a lot of resources. This is why we have quickly given up the first option, which was to connect the output of a state-ofthe-art large vocabulary automatic speech recognition system to the input of our topic recognizer. We have rather decided to investigate and design a lightweight spoken keywords recognition system instead, which is dedicated to work as a pre-processor to the topic recognition module. The efforts concerning the topic recognition module have thus been distributed into both task 4.1 “CMS topic recognition” and subtask 4.5.1 “implicit speech input” as follows: • Task 4.1 deals with the design and development of the inference engine that recognizes topic from a text stream or a sequence of words. It also deals with making the topic recognition fully compliant with the context management system, in particular implementing the IContextSource interface, supporting SPARQL queries and RDF descriptions, and interacting with the context ontology. • Subtask 4.5.1 deals with developing a lightweight keyword spotting module, which can of course be used as a standalone module, but that is primarily designed to extract the most important keywords that can then be passed to the topic recognition module from the user’s speech. Amigo IST-2004-004182 68/114
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User Interface Service Software Developerís Guide - Hitech Projects

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