alpteko / masterthesis

Neural Sign Language By Learning Tokenization

MasterThesis

Neural Sign Language By Learning Tokenization

Tokenization

CNN Training

They produce CNN models.

CNN Feature Extraction

They produce tfrecord and numpy features of the translation dataset. Their form can be right-hand, full frame etc.

NMT Module

It uses OpenNMT-tf library. There are four moddels: Bahdanau, Loung, Transformer, Multi-Source

Training a NMT Module

onmt train_and_eval --model_type [PythonModelFilePath] --config [ConfigYAMLFilePath]

Creating Test and Eval Translation Sentences

Average Models

onmt-average-checkpoints
--model_dir [ModelDirectory]
--output_dir [OutputDirectory]
--max_count 10

Infer Sentences

onmt-main infer
--config conf.yml
--features_file [TestFeatureFilePath]
--predictions_file [OutputPredictonFilePath]
--checkpoint_path [ModelPath(AverageModel)]

Evaluation

Use eval scripts evaluation_utils and pbs Code: evaluation_utils.evaluate(ref_file=,tran_file=, metric=)
Script: python3 pbs.py -reference-file REFERENCE_FILE --baseline-file BASELINE_FILE --sample-size SAMPLE_SIZE

masterthesis's Issues

Instructions for replicate the experiment

Kindly tell me how to run the code of your thesis locally on the Windows or Linux machine. If you provide the step by step instructions to run the code it will be a great help. Also tell me where to find the dataset for the experiment and can we use other sign language dataset for this code.