Witty-Kitty

#!/usr/bin/env python3

import argparse
import epitran

def get_phoneme_string(epi,word):
    phoneme_tuples = epi.word_to_tuples(word)
    num = 0
    phoneme_list = []
    while num < len(phoneme_tuples):

Witty-Kitty

#!/usr/bin/env python3

import argparse
from collections import Counter
from pathlib import Path
import string


def word_frequency(text_directory: Path) -> Counter:
    """Get the word frequency table for a directory of text files."""

Witty-Kitty

baba data - my father
baba iso - your father
baba ise - his/her father
mama mama - my mother
mama nyoko - your mother
mama nyina - his/her mother
kaka musaza - my brother(girl)
kaka mukuru - older brother(boy)
kaka murumuna - younger brother(boy)
dada mushiki - sister to a boy

Witty-Kitty

import gensim
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt

model = gensim.models.KeyedVectors.load_word2vec_format('MUSE/dumped/debug/8gywilp7r1/vectors-rw1.txt')
model2 = gensim.models.KeyedVectors.load_word2vec_format('MUSE/dumped/debug/8gywilp7r1/vectors-lg1.txt')

lg_dict =  {
    "katonda": "god",
    "emu": "one",

Witty-Kitty

import nltk
from nltk.tokenize import word_tokenize
from nltk.text import Text

# read in text data
file = open("crawl-for-parallel-corpora/DataSet/luganda.txt", "r") 
raw = file.read()

# tokenize
tokens = word_tokenize(raw)

Witty-Kitty

package com.example.baseconverter;

import android.os.Bundle;
import android.app.Activity;
import android.content.Intent;
import android.view.View;
import android.widget.Button;
import android.widget.EditText;
import android.widget.TextView;