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-rwxr-xr-xboot/boot.py3
-rw-r--r--boot/vocabcompiler.py71
2 files changed, 1 insertions, 73 deletions
diff --git a/boot/boot.py b/boot/boot.py
index 8697c91..e807beb 100755
--- a/boot/boot.py
+++ b/boot/boot.py
@@ -28,14 +28,13 @@ else:
path = "/usr/local/lib/"
os.environ["PATH"] = path
-import urllib2
-import vocabcompiler
import traceback
lib_path = os.path.abspath('../client')
sys.path.append(lib_path)
from diagnose import Diagnostics
+import vocabcompiler
import speaker as speak
speaker = speak.newSpeaker()
diff --git a/boot/vocabcompiler.py b/boot/vocabcompiler.py
deleted file mode 100644
index f22da1a..0000000
--- a/boot/vocabcompiler.py
+++ /dev/null
@@ -1,71 +0,0 @@
-# -*- coding: utf-8-*-
-"""
- Iterates over all the WORDS variables in the modules and creates a dictionary for the client.
-"""
-
-import os
-import sys
-import glob
-
-lib_path = os.path.abspath('../client')
-mod_path = os.path.abspath('../client/modules/')
-
-sys.path.append(lib_path)
-sys.path.append(mod_path)
-
-import g2p
-
-
-def text2lm(in_filename, out_filename):
- """Wrapper around the language model compilation tools"""
- def text2idngram(in_filename, out_filename):
- cmd = "text2idngram -vocab %s < %s -idngram temp.idngram" % (out_filename,
- in_filename)
- os.system(cmd)
-
- def idngram2lm(in_filename, out_filename):
- cmd = "idngram2lm -idngram temp.idngram -vocab %s -arpa %s" % (
- in_filename, out_filename)
- os.system(cmd)
-
- text2idngram(in_filename, in_filename)
- idngram2lm(in_filename, out_filename)
-
-
-def compile(sentences, dictionary, languagemodel):
- """
- Gets the words and creates the dictionary
- """
-
- m = [os.path.basename(f)[:-3]
- for f in glob.glob(os.path.dirname("../client/modules/") + "/*.py")]
-
- words = []
- for module_name in m:
- try:
- exec("import %s" % module_name)
- eval("words.extend(%s.WORDS)" % module_name)
- except:
- pass # module probably doesn't have the property
-
- words = list(set(words))
-
- # for spotify module
- words.extend(["MUSIC", "SPOTIFY"])
-
- # create the dictionary
- pronounced = g2p.translateWords(words)
- zipped = zip(words, pronounced)
- lines = ["%s %s" % (x, y) for x, y in zipped]
-
- with open(dictionary, "w") as f:
- f.write("\n".join(lines) + "\n")
-
- # create the language model
- with open(sentences, "w") as f:
- f.write("\n".join(words) + "\n")
- f.write("<s> \n </s> \n")
- f.close()
-
- # make language model
- text2lm(sentences, languagemodel)