diff --git a/.vs/acoustic_model/v15/.suo b/.vs/acoustic_model/v15/.suo
index 0b78f7c..92f0791 100644
Binary files a/.vs/acoustic_model/v15/.suo and b/.vs/acoustic_model/v15/.suo differ
diff --git a/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc b/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc
index ad9ae7f..8bb2ce1 100644
Binary files a/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc and b/acoustic_model/__pycache__/defaultfiles.cpython-36.pyc differ
diff --git a/acoustic_model/acoustic_model.pyproj b/acoustic_model/acoustic_model.pyproj
index bbe6bd9..f2c3827 100644
--- a/acoustic_model/acoustic_model.pyproj
+++ b/acoustic_model/acoustic_model.pyproj
@@ -32,7 +32,9 @@
     <Compile Include="defaultfiles.py">
       <SubType>Code</SubType>
     </Compile>
-    <Compile Include="fame_phoneset.py">
+    <Compile Include="fame_asr.py" />
+    <Compile Include="fame_ipa.py" />
+    <Compile Include="fame_test.py">
       <SubType>Code</SubType>
     </Compile>
     <Compile Include="fa_test.py">
diff --git a/acoustic_model/convert_phone_set.py b/acoustic_model/convert_phone_set.py
index d2c1350..0a7ad22 100644
--- a/acoustic_model/convert_phone_set.py
+++ b/acoustic_model/convert_phone_set.py
@@ -20,7 +20,7 @@ def split_word(word, multi_character_phones):
 	
 	Args:
 		word (str): a word written in given phoneset.
-		multi_character_phones (list): the list of multicharacter phones which is considered as one phone. this can be obtained with phoneset definition such as fame_phoneset.py. 
+		multi_character_phones (list): the list of multicharacter phones which is considered as one phone. this can be obtained with phoneset definition such as fame_ipa.py. 
 
 	Returns:
 		(word_seperated) (list): the word splitted in given phoneset. 
diff --git a/acoustic_model/fame_asr.py b/acoustic_model/fame_asr.py
new file mode 100644
index 0000000..8408646
--- /dev/null
+++ b/acoustic_model/fame_asr.py
@@ -0,0 +1,127 @@
+""" definition of the phones to be used. """
+
+# phonese in {FAME}/lexicon/lex.asr
+phoneset = [
+	# vowels
+	'a',
+	'a:',
+	'e',
+	'e:',
+	'i',
+	'i:',
+	'i̯',
+	'o',
+	'o:',
+	'ö',
+	'ö:',
+	'u',
+	'u:',
+	'ü',
+	'ü:',
+	#'ú', # only appears in word 'feeste'(út) and 'gaste'(út) which are 'f e: s t ə' and 'yn' in lex_asr. The pronunciation in Fries may be mistakes so I removed this phone. 
+	'ṷ',
+	'y',
+	'ɔ',
+	'ɔ:',
+	'ɔ̈', 
+	'ɔ̈:',
+	'ə',
+	'ɛ',
+	'ɛ:',
+	'ɪ',
+	'ɪ:',
+
+	# plosives
+	'p', 
+	'b', 
+	't',
+	'd', 
+	'k',
+	'g',
+	'ɡ', # = 'g'
+
+	# nasals
+	'm',
+	'n',
+	'ŋ',
+	
+	# fricatives
+	'f',
+	'v',
+	's',
+	's:',
+	'z',
+	'x',
+	'h',
+	
+	# tap and flip
+	'r',
+	'r:',
+
+	# approximant
+	'j',
+	'l'
+	]
+
+
+## reduce the number of phones.
+# the phones which seldom occur are replaced with another more popular phones.
+# replacements are based on the advice from Martijn Wieling.
+reduction_key = {
+	'y':'i:', 'e':'e:', 'ə:':'ɛ:', 'r:':'r', 'ɡ':'g'
+	}
+# already removed beforehand in phoneset. Just to be sure.
+phones_to_be_removed = ['ú', 's:', 'ɔ̈:']
+
+phoneset_short = [reduction_key.get(i, i) for i in phoneset
+				  if not i in phones_to_be_removed]
+phoneset_short = list(set(phoneset_short))
+phoneset_short.sort()
+
+
+## translation_key to htk format (ascii).
+# phones which gives UnicodeEncodeError when phone.encode("ascii")
+# are replaced with other characters.
+translation_key_asr2htk = {
+	'i̯': 'i_',
+	'ṷ': 'u_',
+
+	# on the analogy of German umlaut, 'e' is used.
+	'ö': 'oe', 'ö:': 'oe:',
+	'ü': 'ue', 'ü:': 'ue:',
+
+	# on the analogy of Chinese...
+	'ŋ': 'ng',
+				
+	# refer to Xsampa. 
+	'ɔ': 'O', 'ɔ:': 'O:', 'ɔ̈': 'Oe',
+	'ɛ': 'E', 'ɛ:': 'E:',
+	'ɪ': 'I', 'ɪ:': 'I:', 
+
+	# it is @ in Xsampa, but that is not handy on HTK.
+	'ə': 'A'
+	}
+phoneset_htk = [translation_key_asr2htk.get(i, i) for i in phoneset_short]
+
+## check
+#for i in phoneset_short:
+#	try:
+#		print("{0} --> {1}".format(i, i.encode("ascii")))
+#	except UnicodeEncodeError:
+#		print(">>> {}".format(i))
+
+
+## the list of multi character phones. 
+# for example, the length of 'a:' is 3, but in the codes it is treated as one letter.
+
+# original.
+multi_character_phones = [i for i in phoneset if len(i) > 1]
+multi_character_phones.sort(key=len, reverse=True)
+
+# phonset reduced.
+multi_character_phones_short = [i for i in phoneset_short if len(i) > 1]
+multi_character_phones_short.sort(key=len, reverse=True)
+
+# htk compatible.
+multi_character_phones_htk = [i for i in phoneset_htk if len(i) > 1]
+multi_character_phones_htk.sort(key=len, reverse=True)
diff --git a/acoustic_model/fame_functions.py b/acoustic_model/fame_functions.py
index eadb879..380f602 100644
--- a/acoustic_model/fame_functions.py
+++ b/acoustic_model/fame_functions.py
@@ -1,5 +1,4 @@
 import os
-os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
 
 import sys
 from collections import Counter
@@ -9,7 +8,7 @@ import numpy as np
 import pandas as pd
 
 import defaultfiles as default
-import fame_phoneset
+from phoneset import fame_ipa
 import convert_phone_set
 
 
@@ -110,14 +109,6 @@ import convert_phone_set
 
 #    return ipa
 
-#def make_filelist(input_dir, output_txt):
-#	""" Make a list of files in the input_dir. """
-#	filenames = os.listdir(input_dir)
-
-#	with open(output_txt, 'w') as fout:
-#		for filename in filenames:
-#			fout.write(input_dir + '\\' + filename + '\n')
-
 
 #def make_htk_dict(word, pronvar_, fileDic, output_type):
 #    """
@@ -179,10 +170,11 @@ def make_hcopy_scp_from_filelist_in_fame(fame_dir, dataset, feature_dir, hcopy_s
 
 				fout.write(wav_file + '\t' + mfc_file + '\n')
 
+	return
 
 
 def load_lexicon(lexicon_file):
-	""" load lexicon file as Data Frame.
+	""" load lexicon file as data frame.
 
 	Args:
 		lexicon_file (path): lexicon in the format of 'word' /t 'pronunciation'.
@@ -196,25 +188,27 @@ def load_lexicon(lexicon_file):
 	return lex
 
 
-def get_phoneset_from_lexicon(lexicon_file, phoneset='asr'):
+def get_phoneset_from_lexicon(lexicon_file, phoneset_name='asr'):
 	""" Make a list of phones which appears in the lexicon. 
 	
 	Args:
 		lexicon_file (path): lexicon in the format of 'word' /t 'pronunciation'.
-		phoneset (str): the phoneset with which lexicon_file is written. 'asr'(default) or 'ipa'.
+		phoneset_name (str): the name of phoneset with which lexicon_file is written. 'asr'(default) or 'ipa'.
 
 	Returns:
 		(list_of_phones) (set): the set of phones included in the lexicon_file.
 
 	"""
-	assert phoneset in ['asr', 'ipa'], 'phoneset should be \'asr\' or \'ipa\''
+	assert phoneset_name in ['asr', 'ipa'], 'phoneset_name should be \'asr\' or \'ipa\''
 
 	lex = load_lexicon(lexicon_file)
-	if phoneset == 'asr':
+	if phoneset_name == 'asr':
 		return set(' '.join(lex['pronunciation']).split(' '))
-	elif phoneset == 'ipa':
+	elif phoneset_name == 'ipa':
 		join_pronunciations = ''.join(lex['pronunciation'])
-		return set(convert_phone_set.split_word(join_pronunciations, fame_phoneset.multi_character_phones_ipa))
+		return set(convert_phone_set.split_word(join_pronunciations, fame_ipa.multi_character_phones))
+
+	return
 
 
 def extract_unknown_phones(ipa, known_phones):
@@ -228,7 +222,7 @@ def extract_unknown_phones(ipa, known_phones):
 		(list_of_phones) (list): unknown phones not included in 'known_phones'.
 
 	"""
-	ipa_split = convert_phone_set.split_word(ipa, fame_phoneset.multi_character_phones_ipa)
+	ipa_split = convert_phone_set.split_word(ipa, fame_ipa.multi_character_phones)
 	return [i for i in ipa_split if not i in known_phones]
 
 
@@ -247,14 +241,14 @@ def get_translation_key(lexicon_file_ipa, lexicon_file_asr):
 	"""
 	lex_ipa = load_lexicon(lexicon_file_ipa)
 	lex_asr = load_lexicon(lexicon_file_asr)
-	phone_unknown = fame_phoneset.phoneset_ipa[:]
+	phone_unknown = fame_ipa.phoneset[:]
 	translation_key = dict()
 	for word in lex_ipa['word']:
 		if np.sum(lex_ipa['word'] == word) == 1 and np.sum(lex_asr['word'] == word) == 1:
 			ipa = lex_ipa[lex_ipa['word'] == word].iat[0, 1]
 			asr = lex_asr[lex_asr['word'] == word].iat[0, 1]
 	
-			ipa_list = convert_phone_set.split_word(ipa, fame_phoneset.multi_character_phones_ipa)
+			ipa_list = convert_phone_set.split_word(ipa, fame_ipa.multi_character_phones)
 			asr_list = asr.split(' ')
 
 			# if there are phones which is not in phone_unknown
@@ -268,13 +262,13 @@ def get_translation_key(lexicon_file_ipa, lexicon_file_asr):
 	return translation_key, list(phone_unknown)
 
 
-def find_phone(lexicon_file, phone, phoneset='ipa'):
+def find_phone(lexicon_file, phone, phoneset_name='ipa'):
 	""" extract rows where the phone is used in the lexicon_file. 
 
 	Args:
 		lexicon_file (path): lexicon in the format of 'word' /t 'pronunciation'.
 		phone (str): the phone to be searched.
-		phoneset (str): the phoneset with which lexicon_file is written. 'asr' or 'ipa'(default).
+		phoneset_name (str): the name of phoneset_name with which lexicon_file is written. 'asr' or 'ipa'(default).
 
 	Returns:
 		extracted (df): rows where the phone is used.
@@ -283,7 +277,7 @@ def find_phone(lexicon_file, phone, phoneset='ipa'):
 		* develop when the phonset == 'asr'.
 
 	"""
-	assert phoneset in ['asr', 'ipa'], 'phoneset should be \'asr\' or \'ipa\''
+	assert phoneset_name in ['asr', 'ipa'], 'phoneset_name should be \'asr\' or \'ipa\''
 	
 	lex = load_lexicon(lexicon_file)
 	
@@ -292,8 +286,8 @@ def find_phone(lexicon_file, phone, phoneset='ipa'):
 
 	extracted = pd.DataFrame(index=[], columns=['word', 'pronunciation'])
 	for index, row in lex_.iterrows():
-		if phoneset == 'ipa':
-			pronunciation = convert_phone_set.split_word(row['pronunciation'], fame_phoneset.multi_character_phones_ipa)
+		if phoneset_name == 'ipa':
+			pronunciation = convert_phone_set.split_word(row['pronunciation'], fame_ipa.multi_character_phones)
 		if phone in pronunciation:
 			extracted_ = pd.Series([row['word'], pronunciation], index=extracted.columns)
 			extracted  = extracted.append(extracted_, ignore_index=True)
diff --git a/acoustic_model/fame_hmm.py b/acoustic_model/fame_hmm.py
index fe319d0..058deaa 100644
--- a/acoustic_model/fame_hmm.py
+++ b/acoustic_model/fame_hmm.py
@@ -8,8 +8,8 @@ import tempfile
 #from collections import Counter
 import time
 
-#import numpy as np
-#import pandas as pd
+import numpy as np
+import pandas as pd
 
 import fame_functions
 import defaultfiles as default
@@ -54,6 +54,10 @@ conv_lexicon	  = 1
 #mkhmmdefs_pl = config['Settings']['mkhmmdefs_pl']
 #FAME_dir	 = config['Settings']['FAME_dir']
 
+#lexicon_dir = os.path.join(default.fame_dir, 'lexicon') 
+#lexicon_ipa = os.path.join(lexicon_dir, 'lex.ipa')
+#lexicon_asr = os.path.join(lexicon_dir, 'lex.asr')
+
 #lex_asr		= FAME_dir + '\\lexicon\\lex.asr'
 #lex_asr_htk = FAME_dir + '\\lexicon\\lex.asr_htk'
 #lex_oov		= FAME_dir + '\\lexicon\\lex.oov'
@@ -111,71 +115,6 @@ if extract_features:
 ## ======================= convert lexicon from ipa to fame_htk =======================
 if conv_lexicon:
 	print('==== convert lexicon from ipa 2 fame ====\n')
-	
-	#dir_out = r'c:\Users\Aki\source\repos\acoustic_model\_tmp'
-	lexicon_dir = os.path.join(default.fame_dir, 'lexicon') 
-	lexicon_ipa = os.path.join(lexicon_dir, 'lex.ipa')
-	lexicon_asr = os.path.join(lexicon_dir, 'lex.asr')
-
-	# get the correspondence between lex_ipa and lex_asr.
-	lex_asr  = fame_functions.load_lexicon(lexicon_asr)
-	lex_ipa  = fame_functions.load_lexicon(lexicon_ipa)		
-	if 1:
-		timer_start = time.time()
-		translation_key, phone_unknown = fame_functions.get_translation_key(lexicon_ipa, lexicon_asr)
-		print("elapsed time: {}".format(time.time() - timer_start))
-
-		np.save('translation_key_ipa2asr.npy', translation_key)
-		np.save('phone_unknown.npy', phone_unknown)
-	else:
-		translation_key = np.load('translation_key_ipa2asr.npy').item()
-		phone_unknown   = np.load('phone_unknown.npy')
-		phone_unknown   = list(phone_unknown)
-
-
-	## manually check the correspondence for the phone in phone_unknown.
-	#p = phone_unknown[0]
-	#lex_ipa_ = find_phone(lexicon_ipa, p, phoneset='ipa')
-
-	#for word in lex_ipa_['word']:
-	#	ipa = lex_ipa[lex_ipa['word'] == word].iat[0, 1]
-	#	if np.sum(lex_asr['word'] == word) > 0:
-	#		asr = lex_asr[lex_asr['word'] == word].iat[0, 1]
-	
-	#		ipa_list = convert_phone_set.split_word(ipa, fame_phoneset.multi_character_phones_ipa)
-	#		asr_list = asr.split(' ')
-	#		if p in ipa_list and (len(ipa_list) == len(asr_list)):
-	#			print("{0}: {1} --> {2}".format(word, ipa_list, asr_list))
-	#			for ipa_, asr_ in zip(ipa_list, asr_list):
-	#				if ipa_ in phone_unknown:
-	#					translation_key[ipa_] = asr_
-	#					phone_unknown.remove(ipa_)
-
-
-	## check if all the phones in lexicon_ipa are in fame_phoneset.py.
-	#timer_start = time.time()
-	#phoneset_lex = get_phoneset_from_lexicon(lexicon_ipa, phoneset='ipa')
-	#print("elapsed time: {}".format(time.time() - timer_start))
-	
-	#phoneset_py = fame_phoneset.phoneset_ipa
-	#set(phoneset_lex) - set(phoneset_py)
-
-	##timer_start = time.time()
-	##extracted = find_phone(lexicon_ipa, 'ⁿ')
-	##print("elapsed time: {}".format(time.time() - timer_start))
-
-
-	# lex.asr is Kaldi compatible version of lex.ipa.
-	# to check... 
-	#lexicon_ipa = pd.read_table(lex_ipa, names=['word', 'pronunciation'])
-	#with open(lex_ipa_, "w", encoding="utf-8") as fout:
-	#	for word, pronunciation in zip(lexicon_ipa['word'], lexicon_ipa['pronunciation']):
-	#		# ignore nasalization and '.'
-	#		pronunciation_ = pronunciation.replace(u'ⁿ', '')
-	#		pronunciation_ = pronunciation_.replace('.', '')
-	#		pronunciation_split = convert_phone_set.split_ipa_fame(pronunciation_)
-	#		fout.write("{0}\t{1}\n".format(word, ' '.join(pronunciation_split)))
-
 	# convert each lexicon from ipa description to fame_htk phoneset.
 	#am_func.ipa2famehtk_lexicon(lex_oov, lex_oov_htk)
 	#am_func.ipa2famehtk_lexicon(lex_asr, lex_asr_htk)
diff --git a/acoustic_model/fame_ipa.py b/acoustic_model/fame_ipa.py
new file mode 100644
index 0000000..4d44f0a
--- /dev/null
+++ b/acoustic_model/fame_ipa.py
@@ -0,0 +1,107 @@
+""" definition of the phones to be used. """
+
+phoneset = [
+	# vowels
+	'i̯',
+	'i̯ⁿ',
+	'y',
+	'i',
+	'i.',
+	'iⁿ',
+	'i:',
+	'i:ⁿ',
+	'ɪ',
+	'ɪⁿ',
+	'ɪ.',
+	#'ɪ:', # not included in lex.ipa
+	'ɪ:ⁿ',
+	'e',
+	'e:',
+	'e:ⁿ',
+	'ə',
+	'əⁿ',
+	'ə:',
+	'ɛ',
+	'ɛ.',
+	'ɛⁿ',
+	'ɛ:',
+	'ɛ:ⁿ',
+	'a',
+	'aⁿ',
+	'a.',
+	'a:',
+	'a:ⁿ',
+	'ṷ',
+	'ṷ.',
+	'ṷⁿ',
+	#'ú', # only appears in word 'feeste'(út) and 'gaste'(út) which are 'f e: s t ə' and 'yn' in lex_asr. The pronunciation in Fries may be mistakes so I removed this phone. 
+	'u',
+	'uⁿ',
+	'u.',
+	'u:',
+	'u:ⁿ',
+	'ü',
+	'ü.',
+	'üⁿ',
+	'ü:',
+	'ü:ⁿ',
+	'o',
+	'oⁿ',
+	'o.',
+	'o:',
+	'o:ⁿ',
+	'ö',
+	'ö.',
+	'öⁿ',
+	'ö:',
+	'ö:ⁿ',
+	'ɔ',
+	'ɔ.',
+	'ɔⁿ',
+	'ɔ:',
+	'ɔ:ⁿ',
+	#'ɔ̈', # not included in lex.ipa 
+	'ɔ̈.',
+	'ɔ̈:',
+
+	# plosives
+	'p', 
+	'b', 
+	't',
+	'tⁿ',
+	'd', 
+	'k',
+	'g',
+	'ɡ', # = 'g'
+
+	# nasals
+	'm',
+	'n',
+	'ŋ',
+	
+	# fricatives
+	'f',
+	'v',
+	's',
+	's:',
+	'z',
+	'zⁿ',
+	'x',
+	'h',
+
+	# tap and flip
+	'r',
+	'r.', # only appears in word 'mearpartijestelsel'(does not exist in lex_asr) and 'tenoarpartij'.   
+	'r:', # only appears in word 'mûsearflearmûs' and 'sjochdêr'.
+
+	# approximant
+	'j',
+	'j.',
+	'l'
+	]
+
+
+## the list of multi character phones. 
+# for example, the length of 'i̯ⁿ' is 3, but in the codes it is treated as one letter.
+multi_character_phones = [i for i in phoneset if len(i) > 1]
+multi_character_phones.sort(key=len, reverse=True)
\ No newline at end of file
diff --git a/acoustic_model/fame_test.py b/acoustic_model/fame_test.py
new file mode 100644
index 0000000..121f4e5
--- /dev/null
+++ b/acoustic_model/fame_test.py
@@ -0,0 +1,93 @@
+import sys
+import os
+os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
+
+import time
+
+import numpy as np
+import pandas as pd
+
+import fame_functions
+import defaultfiles as default
+sys.path.append(default.toolbox_dir)
+from phoneset import fame_ipa, fame_asr
+
+
+lexicon_dir = os.path.join(default.fame_dir, 'lexicon') 
+lexicon_ipa = os.path.join(lexicon_dir, 'lex.ipa')
+lexicon_asr = os.path.join(lexicon_dir, 'lex.asr')
+
+
+## check if all the phones in lexicon.ipa are in fame_ipa.py.
+#timer_start = time.time()
+#phoneset_lex = fame_functions.get_phoneset_from_lexicon(lexicon_ipa, phoneset='ipa')	
+#phoneset_py = fame_ipa.phoneset
+#print("phones which is in lexicon.ipa but not in fame_ipa.py:\n{}".format(
+#	set(phoneset_lex) - set(phoneset_py)))
+#print("elapsed time: {}".format(time.time() - timer_start))
+
+# check which word has the phone. 
+#timer_start = time.time()
+#extracted = find_phone(lexicon_ipa, 'ⁿ')
+#print("elapsed time: {}".format(time.time() - timer_start))
+
+
+## get the correspondence between lex_ipa and lex_asr.	
+lex_asr  = fame_functions.load_lexicon(lexicon_asr)
+lex_ipa  = fame_functions.load_lexicon(lexicon_ipa)		
+if 0:
+	timer_start = time.time()
+	translation_key_ipa2asr, phone_unknown = fame_functions.get_translation_key(lexicon_ipa, lexicon_asr)
+	print("elapsed time: {}".format(time.time() - timer_start))
+
+	np.save(os.path.join('phoneset', 'output_get_translation_key_translation_key.npy'), translation_key_ipa2asr)
+	np.save(os.path.join('phoneset', 'output_get_translation_key_phone_unknown.npy'), phone_unknown)
+else:
+	translation_key_ipa2asr = np.load(os.path.join('phoneset', 'output_get_translation_key_translation_key.npy')).item()
+	phone_unknown   = np.load(os.path.join('phoneset', 'output_get_translation_key_phone_unknown.npy'))
+	phone_unknown   = list(phone_unknown)
+
+# manually check the correspondence for the phone in phone_unknown.
+#p = phone_unknown[0]
+#lex_ipa_ = find_phone(lexicon_ipa, p, phoneset='ipa')
+
+#for word in lex_ipa_['word']:
+#	ipa = lex_ipa[lex_ipa['word'] == word].iat[0, 1]
+#	if np.sum(lex_asr['word'] == word) > 0:
+#		asr = lex_asr[lex_asr['word'] == word].iat[0, 1]
+	
+#		ipa_list = convert_phone_set.split_word(ipa, fame_ipa.multi_character_phones)
+#		asr_list = asr.split(' ')
+#		if p in ipa_list and (len(ipa_list) == len(asr_list)):
+#			print("{0}: {1} --> {2}".format(word, ipa_list, asr_list))
+#			for ipa_, asr_ in zip(ipa_list, asr_list):
+#				if ipa_ in phone_unknown:
+#					translation_key_ipa2asr[ipa_] = asr_
+#					phone_unknown.remove(ipa_)
+translation_key_ipa2asr['ə:'] = 'ə'
+translation_key_ipa2asr['r.'] = 'r'
+translation_key_ipa2asr['r:'] = 'r'
+np.save(os.path.join('phoneset', 'fame_ipa2asr.npy'), translation_key_ipa2asr)
+
+
+## check if all the phones in lexicon.asr are in translation_key_ipa2asr.
+timer_start = time.time()
+phoneset_lex = fame_functions.get_phoneset_from_lexicon(lexicon_asr, phoneset='asr')
+phoneset_lex.remove("")
+phoneset_asr = list(set(translation_key_ipa2asr.values()))
+print("phones which is in lexicon.asr but not in the translation_key_ipa2asr:\n{}".format(
+	set(phoneset_lex) - set(phoneset_asr)))
+print("elapsed time: {}".format(time.time() - timer_start))
+
+## make the translation key between asr to htk.
+#multi_character_phones = [i for i in phoneset_asr if len(i) > 1]
+#multi_character_phones.sort(key=len, reverse=True)
+
+#lexicon_ipa = pd.read_table(lex_ipa, names=['word', 'pronunciation'])
+#with open(lex_ipa_, "w", encoding="utf-8") as fout:
+#	for word, pronunciation in zip(lexicon_ipa['word'], lexicon_ipa['pronunciation']):
+#		# ignore nasalization and '.'
+#		pronunciation_ = pronunciation.replace(u'ⁿ', '')
+#		pronunciation_ = pronunciation_.replace('.', '')
+#		pronunciation_split = convert_phone_set.split_ipa_fame(pronunciation_)
+#		fout.write("{0}\t{1}\n".format(word, ' '.join(pronunciation_split)))
\ No newline at end of file
diff --git a/acoustic_model/fame_phoneset.py b/acoustic_model/phoneset/fame_asr.py
similarity index 88%
rename from acoustic_model/fame_phoneset.py
rename to acoustic_model/phoneset/fame_asr.py
index 2c2387a..01b3ab4 100644
--- a/acoustic_model/fame_phoneset.py
+++ b/acoustic_model/phoneset/fame_asr.py
@@ -1,7 +1,6 @@
 """ definition of the phones to be used. """
 
-## phones in IPA.
-phoneset_ipa = [
+phoneset = [
 	# vowels
 	'i̯',
 	'i̯ⁿ',
@@ -103,5 +102,5 @@ phoneset_ipa = [
 
 ## the list of multi character phones. 
 # for example, the length of 'i̯ⁿ' is 3, but in the codes it is treated as one letter.
-multi_character_phones_ipa = [i for i in phoneset_ipa if len(i) > 1]
-multi_character_phones_ipa.sort(key=len, reverse=True)
\ No newline at end of file
+multi_character_phones = [i for i in phoneset if len(i) > 1]
+multi_character_phones.sort(key=len, reverse=True)
\ No newline at end of file
diff --git a/acoustic_model/phoneset/fame_ipa.py b/acoustic_model/phoneset/fame_ipa.py
new file mode 100644
index 0000000..01b3ab4
--- /dev/null
+++ b/acoustic_model/phoneset/fame_ipa.py
@@ -0,0 +1,106 @@
+""" definition of the phones to be used. """
+
+phoneset = [
+	# vowels
+	'i̯',
+	'i̯ⁿ',
+	'y',
+	'i',
+	'i.',
+	'iⁿ',
+	'i:',
+	'i:ⁿ',
+	'ɪ',
+	'ɪⁿ',
+	'ɪ.',
+	#'ɪ:', # not included in lex.ipa
+	'ɪ:ⁿ',
+	'e',
+	'e:',
+	'e:ⁿ',
+	'ə',
+	'əⁿ',
+	'ə:',
+	'ɛ',
+	'ɛ.',
+	'ɛⁿ',
+	'ɛ:',
+	'ɛ:ⁿ',
+	'a',
+	'aⁿ',
+	'a.',
+	'a:',
+	'a:ⁿ',
+	'ṷ',
+	'ṷ.',
+	'ṷⁿ',
+	#'ú', # only appears in word 'feeste'(út) and 'gaste'(út) which are 'f e: s t ə' and 'yn' in lex_asr. 
+	'u',
+	'uⁿ',
+	'u.',
+	'u:',
+	'u:ⁿ',
+	'ü',
+	'ü.',
+	'üⁿ',
+	'ü:',
+	'ü:ⁿ',
+	'o',
+	'oⁿ',
+	'o.',
+	'o:',
+	'o:ⁿ',
+	'ö',
+	'ö.',
+	'öⁿ',
+	'ö:',
+	'ö:ⁿ',
+	'ɔ',
+	'ɔ.',
+	'ɔⁿ',
+	'ɔ:',
+	'ɔ:ⁿ',
+	#'ɔ̈', # not included in lex.ipa 
+	'ɔ̈.',
+	'ɔ̈:',
+
+	# plosives
+	'p', 
+	'b', 
+	't',
+	'tⁿ',
+	'd', 
+	'k',
+	'g',
+	'ɡ', # = 'g'
+
+	# nasals
+	'm',
+	'n',
+	'ŋ',
+	
+	# fricatives
+	'f',
+	'v',
+	's',
+	's:',
+	'z',
+	'zⁿ',
+	'x',
+	'h',
+
+	# tap and flip
+	'r',
+	'r.', # only appears in word 'mearpartijestelsel'(does not exist in lex_asr) and 'tenoarpartij'.   
+	'r:', # only appears in word 'mûsearflearmûs' and 'sjochdêr'.
+
+	# approximant
+	'j',
+	'j.',
+	'l'
+	]
+
+## the list of multi character phones. 
+# for example, the length of 'i̯ⁿ' is 3, but in the codes it is treated as one letter.
+multi_character_phones = [i for i in phoneset if len(i) > 1]
+multi_character_phones.sort(key=len, reverse=True)
\ No newline at end of file
diff --git a/acoustic_model/phoneset/fame_ipa2asr.npy b/acoustic_model/phoneset/fame_ipa2asr.npy
new file mode 100644
index 0000000..b8852ba
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diff --git a/acoustic_model/phoneset/output_get_translation_key_phone_unknown.npy b/acoustic_model/phoneset/output_get_translation_key_phone_unknown.npy
new file mode 100644
index 0000000..3faddd7
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diff --git a/acoustic_model/phoneset/output_get_translation_key_translation_key.npy b/acoustic_model/phoneset/output_get_translation_key_translation_key.npy
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index 0000000..4eaf1b7
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