acoustic_model.sln

@@ -16,7 +16,6 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution
 		..\forced_alignment\forced_alignment\pronunciations.py = ..\forced_alignment\forced_alignment\pronunciations.py
 		..\toolbox\pyHTK.py = ..\toolbox\pyHTK.py
 		..\forced_alignment\forced_alignment\pyhtk.py = ..\forced_alignment\forced_alignment\pyhtk.py
-		reus-test\reus-test.py = reus-test\reus-test.py
 		..\forced_alignment\forced_alignment\scripts.py = ..\forced_alignment\forced_alignment\scripts.py
 		..\..\..\..\..\Python36-32\Lib\site-packages\novoapi\backend\session.py = ..\..\..\..\..\Python36-32\Lib\site-packages\novoapi\backend\session.py
 		..\forced_alignment\forced_alignment\tempfilename.py = ..\forced_alignment\forced_alignment\tempfilename.py

acoustic_model/acoustic_model.pyproj

@@ -4,7 +4,8 @@
     <SchemaVersion>2.0</SchemaVersion>
     <ProjectGuid>4d8c8573-32f0-4a62-9e62-3ce5cc680390</ProjectGuid>
     <ProjectHome>.</ProjectHome>
-    <StartupFile>forced_aligner_comparison.py</StartupFile>
+    <StartupFile>
+    </StartupFile>
     <SearchPath>
     </SearchPath>
     <WorkingDirectory>.</WorkingDirectory>
@@ -35,9 +36,6 @@
     <Compile Include="fa_test.py">
       <SubType>Code</SubType>
     </Compile>
-    <Compile Include="forced_aligner_comparison.py">
-      <SubType>Code</SubType>
-    </Compile>
     <Compile Include="novoapi_forced_alignment.py">
       <SubType>Code</SubType>
     </Compile>

acoustic_model/check_novoapi.py

@@ -10,13 +10,14 @@ import shutil
 import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
+
 from sklearn.metrics import confusion_matrix
 from sklearn.metrics import accuracy_score
 import novoapi 
 
 import defaultfiles as default
 sys.path.append(default.forced_alignment_module_dir)
-from forced_alignment import convert_phone_set
+from forced_alignment import pyhtk, convert_phone_set
 #import acoustic_model_functions as am_func
 import convert_xsampa2ipa
 import novoapi_functions
@@ -46,6 +47,10 @@ david_suggestion = ['ɔː', 'ɪː', 'iː', 'œː', 'ɛː', 'w']
 ## read pronunciation variants.
 stimmen_transcription_ = pd.ExcelFile(default.stimmen_transcription_xlsx)
 df = pd.read_excel(stimmen_transcription_, 'frequency')
+#for xsampa, ipa in zip(df['X-SAMPA'], df['IPA']):
+#    ipa_converted = convert_xsampa2ipa.xsampa2ipa(mapping, xsampa)
+#    if not ipa_converted == ipa:
+#        print('{0}: {1} - {2}'.format(xsampa, ipa_converted, ipa))
 transcription_ipa = list(df['IPA'])
 
 # transcription mistake?
@@ -58,7 +63,6 @@ for ipa in transcription_ipa:
 	ipa = ipa.replace(':', 'ː')
 	ipa = convert_phone_set.split_ipa(ipa)
 
-	# list of phones not in novo70 phoneset.
 	not_in_novo70_ = [phone for phone in ipa 
 				   if not phone in phoneset_ipa and not phone in david_suggestion]
 	not_in_novo70_ = [phone.replace('sp', '') for phone in not_in_novo70_]
@@ -102,10 +106,6 @@ df = pd.read_excel(stimmen_transcription_, 'original')
 
 # mapping from ipa to xsampa
 mapping = convert_xsampa2ipa.load_converter('xsampa', 'ipa', default.ipa_xsampa_converter_dir)
-#for xsampa, ipa in zip(df['X-SAMPA'], df['IPA']):
-#    ipa_converted = convert_xsampa2ipa.xsampa2ipa(mapping, xsampa)
-#    if not ipa_converted == ipa:
-#        print('{0}: {1} - {2}'.format(xsampa, ipa_converted, ipa))
 
 ipas     = []
 famehtks = []
@@ -153,12 +153,12 @@ for word in word_list:
 
 
 ## ===== forced alignment =====
-rozen_dir = r'c:\Users\Aki\source\repos\acoustic_model\rozen-test'
+reus_dir = r'C:\OneDrive\Desktop\Reus'
 if forced_alignment_novo70:
 	Results = pd.DataFrame(index=[],
 		columns=['filename', 'word', 'xsampa', 'ipa', 'result_ipa', 'result_novo70', 'llh'])
 	#for word in word_list:
-	for word in ['Rozen']:
+	for word in ['Reus']:
 		# pronunciation variants top 3
 		df_per_word_ = df_per_word[df_per_word['word']==word]
 		df_per_word_ = df_per_word_.sort_values('frequency', ascending=False)
@@ -208,35 +208,37 @@ if forced_alignment_novo70:
 			wav_file = os.path.join(default.stimmen_wav_dir, filename)
 			if os.path.exists(wav_file):
 				# for Martijn
-				shutil.copy(wav_file, os.path.join(rozen_dir, filename))
+				#shutil.copy(wav_file, os.path.join(reus_dir, filename))
 
-		#		pronunciation_ipa_ = [ipa.replace(':', 'ː') for ipa in pronunciation_ipa]
-		#		result = novoapi_functions.forced_alignment(wav_file, word, pronunciation_ipa_)
-		#		result_ipa, result_novo70, llh = novoapi_functions.result2pronunciation(result, word)
-		#		result_ = pd.Series([
-		#			sample['filename'],
-		#			sample['word'],
-		#			sample['xsampa'],
-		#			sample['ipa'],
-		#			' '.join(result_ipa),
-		#			' '.join(result_novo70),
-		#			llh
-		#			], index=results.columns)
-		#		results = results.append(result_, ignore_index = True)
-		#		print('{0}/{1}: answer {2} - prediction {3}'.format( 
-		#	 i+1, len(samples), result_['ipa'], result_['result_ipa']))
-		#	#results.to_excel(os.path.join(default.stimmen_dir, 'results.xlsx'), encoding="utf-8")
-		#if len(results) > 0:
-		#	Results = Results.append(results, ignore_index = True)
-		#Results.to_excel(os.path.join(default.stimmen_result_novoapi_dir, 'Results.xlsx'), encoding="utf-8")
+				pronunciation_ipa_ = [ipa.replace(':', 'ː') for ipa in pronunciation_ipa]
+				result = novoapi_functions.forced_alignment(wav_file, word, pronunciation_ipa_)
+				result_ipa, result_novo70, llh = novoapi_functions.result2pronunciation(result, word)
+				result_ = pd.Series([
+					sample['filename'],
+					sample['word'],
+					sample['xsampa'],
+					sample['ipa'],
+					' '.join(result_ipa),
+					' '.join(result_novo70),
+					llh
+					], index=results.columns)
+				results = results.append(result_, ignore_index = True)
+				print('{0}/{1}: answer {2} - prediction {3}'.format( 
+			 i+1, len(samples), result_['ipa'], result_['result_ipa']))
+			results.to_excel(os.path.join(reus_dir, 'results.xlsx'), encoding="utf-8")
+		if len(results) > 0:
+			Results = Results.append(results, ignore_index = True)
+		Results.to_excel(os.path.join(default.stimmen_dir, 'Results.xlsx'), encoding="utf-8")
 else:
-	Results_xlsx = pd.ExcelFile(os.path.join(default.stimmen_result_novoapi_dir, 'Results.xlsx'), encoding="utf-8")
+	Results_xlsx = pd.ExcelFile(os.path.join(default.stimmen_dir, 'Results.xlsx'), encoding="utf-8")
 	Results = pd.read_excel(Results_xlsx, 'Sheet1')
 
 
 ## ===== analysis =====
+#result_novoapi_dir = os.path.join(default.stimmen_dir, 'result', 'novoapi')
 #for word in word_list:
 #	if not word == 'Oog':
+
 #		Results_ = Results[Results['word'] == word]
 #		y_true  = list(Results_['ipa'])
 #		y_pred_ = [ipa.replace(' ', '') for ipa in list(Results_['result_ipa'])]
@@ -247,4 +249,4 @@ else:
 #		plt.figure()
 #		output_confusion_matrix.plot_confusion_matrix(cm, pronunciation_variants, normalize=False)
 #		#plt.show()
-#		plt.savefig(os.path.join(default.stimmen_result_novoapi_dir, word + '.png'))
+#		plt.savefig(os.path.join(result_novoapi_dir, word + '.png'))

acoustic_model/defaultfiles.py

@@ -31,12 +31,6 @@ ipa_xsampa_converter_dir    = os.path.join(repo_dir, 'ipa-xsama-converter')
 forced_alignment_module_dir = os.path.join(repo_dir, 'forced_alignment')
 accent_classification_dir   = os.path.join(repo_dir, 'accent_classification', 'accent_classification')
 
-htk_config_dir = r'c:\Users\Aki\source\repos\forced_alignment\forced_alignment\data\htk\preset_models\aki_dutch_2017'
-config_hvite = os.path.join(htk_config_dir, 'config.HVite')
-#acoustic_model = os.path.join(htk_config_dir, 'hmmdefs.compo')
-acoustic_model = r'c:\cygwin64\home\Aki\acoustic_model\model\barbara\hmm128-2\hmmdefs.compo'
-phonelist_txt = os.path.join(htk_config_dir, 'phonelist.txt')
-
 WSL_dir   = r'C:\OneDrive\WSL'
 fame_dir        = os.path.join(WSL_dir, 'kaldi-trunk', 'egs', 'fame')
 fame_s5_dir     = os.path.join(fame_dir, 's5')
@@ -49,7 +43,6 @@ stimmen_data_dir = os.path.join(stimmen_dir, 'data')
 #stimmen_wav_dir  = os.path.join(stimmen_dir, 'wav')
 # 16 kHz
 stimmen_wav_dir  = r'c:\OneDrive\WSL\kaldi-trunk\egs\fame\s5\corpus\stimmen'
-stimmen_result_novoapi_dir = os.path.join(stimmen_dir, 'result', 'novoapi')
 
 stimmen_transcription_xlsx = os.path.join(stimmen_data_dir, 'Frisian Variants Picture Task Stimmen.xlsx')
 phonelist_friesian_txt     = os.path.join(experiments_dir, 'friesian', 'acoustic_model', 'config', 'phonelist_friesian.txt')

acoustic_model/forced_aligner_comparison.py

@@ -1,42 +0,0 @@
-import os
-os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
-import sys
-
-import defaultfiles as default
-sys.path.append(default.forced_alignment_module_dir)
-from forced_alignment import pyhtk, convert_phone_set, scripts
-
-reus_dir  = r'c:\Users\Aki\source\repos\acoustic_model\reus-test'
-wav_dir   = reus_dir
-wav_files = ['reus1008-reus.wav', 
-			 'reus1167-man.wav',
-			 'reus3768-mantsje.wav']
-
-word = 'reus'
-pronunciation_ipa = ['rø:s', 'mɑn', 'mɑntsjə']
-
-for wav_file in wav_files:
-	file_lab = os.path.join(reus_dir, wav_file.replace('.wav', '.lab'))
-	file_dic = os.path.join(reus_dir, wav_file.replace('.wav', '.dic'))
-	file_txt = os.path.join(reus_dir, wav_file.replace('.wav', '.txt'))
-
-	# output htk dict file
-	with open(file_dic, 'w', encoding="utf-8") as f:
-		for ipa in pronunciation_ipa:
-			cgn = convert_phone_set.ipa2cgn([ipa.replace(':', 'ː')])
-			barbara = convert_phone_set.cgn2barbara(cgn)
-			f.write(word.upper() + '\t' + barbara + '\n')
-
-	# output htk label file.
-	pyhtk._create_label_file(word, file_lab)
-
-	scripts.run_command([
-					'HVite','-T', '1', 
-					'-a', 
-					'-C', default.config_hvite,
-					'-H', default.acoustic_model, 
-					'-m', 
-					'-i', file_txt, 
-					#'-S', script_file, 
-					file_dic, default.phonelist_txt, os.path.join(wav_dir, wav_file)
-				])

acoustic_model/novoapi_functions.py

@@ -7,7 +7,7 @@ import json
 from novoapi.backend import session
 
 import os
-#os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
+os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
 import defaultfiles as default
 
 

reus-test/reus1008-reus.dic

@@ -1,3 +0,0 @@
-REUS	r eu s
-REUS	m ac n
-REUS	m ac n t s j @

reus-test/reus1008-reus.lab

@@ -1 +0,0 @@
-REUS

reus-test/reus1008-reus.txt

@@ -1,6 +0,0 @@
-#!MLF!#
-"c:/Users/Aki/source/repos/acoustic_model/reus-test/reus1008-reus.rec"
-0 9700000 r -12463.852539 REUS
-9700000 12800000 eu -3622.108887
-12800000 26250001 s -17303.216797
-.

reus-test/reus1167-man.dic

@@ -1,3 +0,0 @@
-REUS	r eu s
-REUS	m ac n
-REUS	m ac n t s j @

reus-test/reus1167-man.lab

@@ -1 +0,0 @@
-REUS

reus-test/reus1167-man.txt

@@ -1,10 +0,0 @@
-#!MLF!#
-"c:/Users/Aki/source/repos/acoustic_model/reus-test/reus1167-man.rec"
-0 150000 m -230.057571 REUS
-150000 300000 ac -250.994858
-300000 450000 n -202.377716
-450000 4600000 t -5128.984375
-4600000 5050000 s -711.338501
-5050000 5450000 j -564.730591
-5450000 16049999 @ -13249.787109
-.

reus-test/reus3768-mantsje.dic

@@ -1,3 +0,0 @@
-REUS	r eu s
-REUS	m ac n
-REUS	m ac n t s j @

reus-test/reus3768-mantsje.lab

@@ -1 +0,0 @@
-REUS

reus-test/reus3768-mantsje.txt

@@ -1,10 +0,0 @@
-#!MLF!#
-"c:/Users/Aki/source/repos/acoustic_model/reus-test/reus3768-mantsje.rec"
-0 150000 m -217.347229 REUS
-150000 1150000 ac -1266.293579
-1150000 1650000 n -583.382568
-1650000 11100000 t -11259.270508
-11100000 11250000 s -247.939255
-11250000 11550000 j -445.511444
-11550000 24150000 @ -16769.048828
-.

rozen-test/rozen-test.py

@@ -1,119 +0,0 @@
-#!/usr/bin/env python
-import os
-os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
-
-import argparse
-import json
-
-from novoapi.backend import session
-
-p = argparse.ArgumentParser()
-p.add_argument("--user", default='martijn.wieling')
-p.add_argument("--password", default='xxxxx')
-args = p.parse_args()
-
-rec = session.Recognizer(grammar_version="1.0", lang="nl", snodeid=101, user=args.user, password=args.password, keepopen=True)
-
-grammar = {
-  "type": "confusion_network",
-  "version": "1.0",
-  "data": {
-    "kind": "sequence",
-    "elements": [
-      {
-        "kind": "word",
-        "pronunciation": [
-          {
-            "phones": [
-              "r",
-              "eu0",
-              "s"
-            ],
-            "id": 0
-          }
-          ,
-          {
-            "phones": [
-              "m",
-              "a0",
-              "n"
-            ],
-            "id": 1
-          }
-		   ,
-          {
-            "phones": [
-              "m",
-              "a0",
-              "n",
-              "t",
-              "s",
-              "y",
-              "ax"
-            ],
-            "id": 2
-          }
-        ],
-        "label": "reus"
-      }
-    ]
-  },
-  "return_objects": [
-    "grammar"
-  ],
-  "phoneset": "novo70"
-}
-
-res = rec.setgrammar(grammar)
-#print "Set grammar result", res
-
-
-## === novoapi/backend/session.py ===
-#import wave
-#import time
-#from novoapi.backend.session import rpcid, segmentation
-
-#wavf = "reus1008-reus.wav"
-#w = wave.open(wavf, 'r')
-#nchannels, sampwidth, framerate, nframes, comptype, compname = w.getparams()
-#buf = w.readframes(nframes)
-#w.close()
-
-#buffer_size = 4096
-#nbytes_sent = 0
-#start = time.time()
-#for j in range(0, len(buf), buffer_size):
-#    audio_packet = buf[j:j + buffer_size]
-#    nbytes_sent += len(audio_packet)
-#    rec.conn.send_binary(audio_packet)
-#rec.conn.send(json.dumps({"jsonrpc": "2.0", "method": "get_result", "id": rpcid.next()}))
-#print(rpcid.next())
-#rec.last_message = rec.conn.recv() 
-#message = json.loads(rec.last_message)
-#result = session.segmentation(message["result"]["words"])
-#result.export()
-## ====================================
-
-def result2pronunciation(result, word):
-	#result_ = res.export()[1]
-	result_ = [result[i] for i in range(len(result)) if result[i]['label'] == word] 
-	llh = result_[0]['llh']
-	phones = result_[0]['phones']
-	pronunciation = [phone['label'] for phone in phones]
-	return pronunciation, llh
-
-
-res = rec.recognize_wav("reus1008-reus.wav")
-#print "\n\n\nThe pronounced word in reus1008-reus.wav is: REUS\n\n"
-#print "Recognition result:", json.dumps(res.export(), indent=4)
-result2pronunciation(res.export(), 'reus')
-
-#print "\n\n\nThe pronounced word in reus1167-man.wav is: MAN\n\n"
-res2 = rec.recognize_wav("reus1167-man.wav")
-#print "Recognition result:", json.dumps(res2.export(), indent=4)
-result2pronunciation(res2.export(), 'reus')
-
-#print "\n\n\nThe pronounced word in reus3768-mantsje.wav is: MANTSJE\n\n"
-res3 = rec.recognize_wav("reus3768-mantsje.wav")
-#print "Recognition result:", json.dumps(res3.export(), indent=4)
-result2pronunciation(res3.export(), 'reus')