README.md

SLU

in SLU\data\temp\train.txt:

you can see:

i+1: paragraph id

i+2: lecturer id

i+3: content of dialogue

i+4: intents(labels)

first, you need configuration SLU/code/conf.ini

MAX_MEMORY: number of memory(frozen)

MAX_NB_LABELS: number of label set in train dataset

MAX_NB_WORDS: number of word in train dataset

MAX_SEQUENCE_LENGTH: length of max sequence in train dataset

TEXT_DATA_DIR: path of data for save

TYPE: type of the word embedding

EMBEDDING_DIM: dim of word embedding

MINI_VECTOR: save path of word embedding dict for all words in train dataset

VECTOR_DIR: the model of word embedding that you can get in https://nlp.stanford.edu/projects/glove/

second, you need execute SLU/code/multi_turn.py

python multi_turn.py train.txt valid.txt [train, valid, test] exp: if you want train model, you can:

python multi_turn.py D:\file\intent_model\SLU\data\temp\train.txt '' train if you want valid model, you can:

python multi_turn.py D:\file\intent_model\SLU\data\temp\train.txt D:\file\intent_model\SLU\data\temp\valid.txt valid if you want test model, you can:

python multi_turn.py D:\file\intent_model\SLU\data\temp\train.txt D:\file\intent_model\SLU\data\temp\valid.txt test