Language Recognizer

Sophia Davis Final Project for Carleton NLP, Fall 2013

For detailed information on methods and results, please see report.pdf

To train models:
codebook method: python train_recognizer_codebook.py language1.wav language1_name language2.wav language2_name ...
simple method:
python train_recognizer.py language1.wav language1_name language2.wav language2_name ...

To test sound recordings:
codebook method: python recognizer_codebook.py 'english_obama_clean_1.wav'
simple method: python recognizer.py 'english_obama_clean_1.wav'

The current languages.dat and languages_codebook.dat have been trained on the following:

english_obama_clean_1.wav
english_sweden_clean_2.wav
french_obama_clean_1.wav french_sweden_clean_3.wav
russian_obama_clean_2.wav
russian_sweden_clean_1.wav

The following scripts can be used to train and test many permutations of training and test sets: script_2speakers.py
script_3speakers.py (unfamiliar-speaker model)
script_4speakers.py

Sound files are clips of translations of speeches from the Sept. 24th, 2013 UN General Assembly.