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Wordsmith.py
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Wordsmith.py
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# The MIT License (MIT)
# Copyright (c) 2013 Yat Choi
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
import nltk
import DataReader
from PhoneticBucket import PhoneticBucket
nltk.data.path.insert(0,'./nltk_data/')
entries = nltk.corpus.cmudict.entries()
dictionary = dict(entries)
pronDict = dict()
bucket = PhoneticBucket()
wordlist = dictionary.keys()
def setup():
bucket.setBucket(DataReader.loadBucket())
wordlist.extend(DataReader.collocationEntries())
for w in wordlist:
addStress(tokenize(w))
def addStress(pron):
stress = []
phonecount = 0
for phone in pron:
for char in phone:
if char.isdigit():
stress.append([int(char),phone, phonecount])
phonecount = phonecount + 1
pronDict[str(pron)] = stress
def getStress(pron):
if not str(pron) in pronDict:
addStress(pron)
return pronDict[str(pron)]
def getPron(inputWord):
if not inputWord in dictionary:
return False
inputPron = dictionary[inputWord]
# if inputPron[-1] == 'NG' and len(getStress(inputPron)) > 1:
# inputPron[-1] = 'N'
return inputPron
def tokenize(word):
pron = []
wordsplit = word.split()
for w in wordsplit:
if (not w in dictionary):
return []
else:
pron.extend(getPron(w))
return pron
def getRelevantWords(word):
return bucket.getListFromWord(word)