File model approach to optimize the performance of Tree Adjoining Grammar based Machine Translation

The growing pace of information technology demands fast operation for communication and other related applications. After having a successful Machine Translation System [MTS], it has been felt to optimize the performance of Machine Translation for its real-time uses. The considered MTS is Tree Adjoining Grammar [TAG] based system. An approach has been experimented to use File model instead of Database model for fast streaming of grammar into memory and operation. This model provides an efficient and a systematic way of encapsulating language resource with engineering solution to develop the speedy MTS. The computational experiments demonstrate that substantial performance in terms of time and memory has been obtained by using this approach.