We have developed Interaction Builder (IB), a rapid prototyping tool for constructing web-based Multi-Modal Interaction (MMI) applications. The goal of IB is making it easy to develop MMI applications with speech recognition, life-like agents, speech synthesis, web browsing, etc. For this purpose, IB supports the following interface and functions: (1) GUI for implementing MMI systems without the details of MMI and MMI description language, (2) functionalities of handling synchronized multimodal inputs/outputs, (3) a test run mode for run-time testing. The results of evaluation tests showed that the application development cycle using IB was significantly shortened in comparison with the time using a text editor both for MMI description language experts and for beginners.

This paper proposes a method for cursive handwritten word recognition. Cursive word recognition generally consists of segmentation of a cursive word, character recognition and word recognition. Traditional approaches detect one candidate of segmentation point between characters, and cut the touching characters at the point [1]. But, it is difficult to detect a correct segmentation point between characters in cursive word, because form of touching characters varies greatly by cases. In this research, we determine multiple candidates as segmentation points between characters. Character recognition and word recognition decide which candidate is the most plausible touching point. As a result of the experiment, at the character recognition stage, recognition rate was 75.7%, while cumulative recognition rate within best three candidates was 93.7%. In word recognition, recognition rate was 79.8%, while cumulative recognition rate within best five candidates was 91.7% when lexicon size is 50. The processing speed is about 30 sec/word on SPARC station 5.