Sentence Generation and Correction

This is a submission to the second assignment of McGill University's ECSE 526 - Artificial Intelligence course. Details can be found here.

Setup

To run this, all one needs is Python 3.4 or above and pip3.

To install dependencies, simply run:

pip3 install -r requirements.txt

Details

This assignment has two parts:

Sentence Generation

Sentence are randomly generated using Markov models defined in data.

To run, simply execute:

python3 generator.py

More detailed output can be displayed using th e -v or --verbose flags.

Sentence Correction

Sentence are corrected using a Hidden Markov Model (HMM) and Viterbi's algorithm. The intput is read from stdin, and the output is the most likely sentence based on a first-order Markov chain and the Levenshtein distance.

To run, simply execute:

python3 corrector.py

Input can also be piped in as follows:

echo "Tell moi" | python3 corrector.py
# Tell me

More detailed output can be displayed using th e -v or --verbose flags.

Accuracy

Note that the accuracy of both the sentences generated and the corrections is only dependent on the data set used. Valid English words will be "corrected" if they are not found in the data set. Take a look here for details on how to use your own dataset.