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Spoken Language Understanding (SLU) Module for Movie Domain using NL-SPARQL Data Set

Second Project

/Second/start.sh: This script call Theano tool in order to execute all models, its requires one parameter, if negative number, run all models, if positive between 1..7, run a specific configuration file.

/Second/files.sh: Create the label and word dictionary, using the initial training dataset, split it in a training dataset with the 75% of the sentences and in a validation dataset with the remaining 25%.

/Second/result/ output evaluation result

/Second/rnn_slu/data/: Train e Test files

Example:

./Start.sh -1 run all models

./Start.sh 2 run model: config_2.cfg

First Project

/First/code/start.sh: Used to start the Train/Test process, contains 3 parameters, smoothing, grammar and threshold. The parameter smoothing represents the smoothing method that can be ( 1=Absolute, 2=Katz, 3=Kneser Ney, 4=Pre-smoothed, 5=unsmoothed, 6=Witten bell). The grammar parameter represents the n-gram order the in- terval is between 1-5, the last parame- ter represents the Cut-off threshold, with 0 without cut-off. if smoothing method is negative,the script run all possible combination of method n-grammar and threshold.

/First/code/trainTest.sh: Script used to train and test the ML.

/First/code/transducer_UNK.sh: Create the Transducer files for known tokens.

/First/code/transducer.sh: Create the Transducer files for Unknown tokens.

/First/result/ output evaluation result

/First/data/: Train e Test files

Example:

./Start.sh 1 3 0 run smoothing method Absolute. grammar order 3. cut-off No.

./Start.sh -1 run all combinations smoothing method [1-6] / grammar order [1-5] / cut-off threshold [0-2]