Neural network model that predicts the number of syllables in an English word. It shows its creation end-to-end: from data collection to evaluation of various models. This is the model design followed as part of the making of the reading level scoring app Readgauge.
This repo has both the data and the code to run the models. All you need to do is to meet the prerequisites.
Python>=3.8.6
nltk
pandas
numpy
tensorflow
Run the jupyter notebook cells in train.ipynb under /preprocess/syllable_count_dict_creation
python ./ML/preprocess/data_synthesizer/data_synthesizer.py
Run the jupyter notebook cells in train.ipynb under training/feedforward or under training/blstm.
These model were trained to find one to be integrated to to the Readgauge client-side web app. It runs live here and its repository is here.
The syllableCountDict dataset contains the syllable count of each word
It was created using nltk's built-in CMU dictionary.
The Carnegie Mellon Pronouncing Dictionary [cmudict.0.6] Copyright 1998 Carnegie Mellon University