Prototype 4 (Technical updates)

After a series of tests with the Antelope tagger, I found that it still has a lot of bugs. Hence, I decided to use the Stanford parser as a tagger in order to perform shallow parsing to the returned VPF trigger. It seems to be working OK, though its much slower than the Antelope tagger.

I also changed the flat textual database with the an XML one that provides a more structured way to access its contents. For example,

<sentances id="2">
<text>Can we begin the tour please</text>
<predicates2>begin</predicates2>
<predicates2>please</predicates2>
<Deep_Syntax name="Subject">We</Deep_Syntax>
<Deep_Syntax name="Subject">Tour</Deep_Syntax>
</sentances>

A pilot with three participants showed that the search algorithm works effectively. In addition, the following design alternations were suggested:

1) Break down the presentations each user has to listen (and ask questions) into parts. That way question asking can be focused on certain parts and not on the whole of the presentation

2) Create a castle window that will help users visualize the presented information. I used detailed 3D panoramic pictures from each location in the castle, to help them achieve this goal (see screenshot)

3) Include a stop and pause button on the interface. Participants can pause the text to speech synthesis or simply stop it if they find i annoying.

4) Search google and wikipedia using natural language for words and terms that are unknown to the user. This feature was simulated in the current system. 

This system will be evaluated with 15 participants at Middlesex University.

Future Work:

1) Extend the current algorithm to include semantics. Such system will match the user’s input with existing triggers in the DB at the semantic level.

2) Replace the XML database with an SQL one. Although the XML DB works fine, it has to load all phrases and parses into RAM. With a static MySQL database I can avoid that.

3) In the current implementation, if the system fails to match an input with a trigger in the DB, it will return “I am not sure if I understand your question please re phrase”. Parsing of the input though, is usually successful. The idea here, is to allow the system to actually learn the questions the previous users asked. For example, if the first user asks “What is a pergola?” and the system doesn’t have an answer, it should be able to dynamically update its DB’s and return an answer by searching the WWW. That way, the more questions users ask the more “intelligent” the system it becomes.