diff --git a/.vs/VSWorkspaceState.json b/.vs/VSWorkspaceState.json
index e3b564f..5917527 100644
--- a/.vs/VSWorkspaceState.json
+++ b/.vs/VSWorkspaceState.json
@@ -3,6 +3,6 @@
     "",
     "\\text"
   ],
-  "SelectedNode": "\\train.py",
+  "SelectedNode": "\\text\\cleaners.py",
   "PreviewInSolutionExplorer": false
 }
\ No newline at end of file
diff --git a/.vs/slnx.sqlite b/.vs/slnx.sqlite
index d7477be..c5f2171 100644
Binary files a/.vs/slnx.sqlite and b/.vs/slnx.sqlite differ
diff --git a/.vs/vits/FileContentIndex/211e1f28-c38f-4713-a77b-09725dc4fdd8.vsidx b/.vs/vits/FileContentIndex/211e1f28-c38f-4713-a77b-09725dc4fdd8.vsidx
new file mode 100644
index 0000000..ee3c84e
Binary files /dev/null and b/.vs/vits/FileContentIndex/211e1f28-c38f-4713-a77b-09725dc4fdd8.vsidx differ
diff --git a/.vs/vits/v17/.suo b/.vs/vits/v17/.suo
index 37f2da6..5595f53 100644
Binary files a/.vs/vits/v17/.suo and b/.vs/vits/v17/.suo differ
diff --git a/data_utils.py b/data_utils.py
index 21064b4..4855699 100644
--- a/data_utils.py
+++ b/data_utils.py
@@ -215,7 +215,7 @@ def get_audio(self, filename):
                 self.sampling_rate, self.hop_length, self.win_length,
                 center=False)
             spec = torch.squeeze(spec, 0)
-            torch.save(spec, spec_filename, _use_new_zipfile_serialization=False)
+            torch.save(spec, spec_filename)
         return spec, audio_norm
 
     def get_text(self, text):
diff --git a/text/__init__.py b/text/__init__.py
index d89aa75..48ae82f 100644
--- a/text/__init__.py
+++ b/text/__init__.py
@@ -1,13 +1,11 @@
 """ from https://github.com/keithito/tacotron """
 from text import cleaners
+from text.symbols import symbols
 
 
-def initialize(symbols):
-  # Mappings from symbol to numeric ID and vice versa:
-  global _symbol_to_id
-  global _id_to_symbol
-  _symbol_to_id = {s: i for i, s in enumerate(symbols)}
-  _id_to_symbol = {i: s for i, s in enumerate(symbols)}
+# Mappings from symbol to numeric ID and vice versa:
+_symbol_to_id = {s: i for i, s in enumerate(symbols)}
+_id_to_symbol = {i: s for i, s in enumerate(symbols)}
 
 
 def text_to_sequence(text, cleaner_names):
diff --git a/text/cleaners.py b/text/cleaners.py
index 690585c..00db1c7 100644
--- a/text/cleaners.py
+++ b/text/cleaners.py
@@ -295,7 +295,44 @@ def japanese_cleaners(text):
 
 
 def japanese_cleaners2(text):
-  return japanese_cleaners(text).replace('ts','ʦ')
+  '''Pipeline for notating accent in Japanese text.'''
+  '''Reference https://r9y9.github.io/ttslearn/latest/notebooks/ch10_Recipe-Tacotron.html'''
+  sentences = re.split(_japanese_marks, text)
+  marks = re.findall(_japanese_marks, text)
+  text = ''
+  for i, sentence in enumerate(sentences):
+    if re.match(_japanese_characters, sentence):
+      if text!='':
+        text+=' '
+      labels = pyopenjtalk.extract_fullcontext(sentence)
+      for n, label in enumerate(labels):
+        phoneme = re.search(r'\-([^\+]*)\+', label).group(1)
+        if phoneme not in ['sil','pau']:
+          text += phoneme.replace('ch','ʧ').replace('sh','ʃ').replace('cl','Q').replace('ts','ʦ')
+        else:
+          continue
+        n_moras = int(re.search(r'/F:(\d+)_', label).group(1))
+        a1 = int(re.search(r"/A:(\-?[0-9]+)\+", label).group(1))
+        a2 = int(re.search(r"\+(\d+)\+", label).group(1))
+        a3 = int(re.search(r"\+(\d+)/", label).group(1))
+        if re.search(r'\-([^\+]*)\+', labels[n + 1]).group(1) in ['sil','pau']:
+          a2_next=-1
+        else:
+          a2_next = int(re.search(r"\+(\d+)\+", labels[n + 1]).group(1))
+        # Accent phrase boundary
+        if a3 == 1 and a2_next == 1:
+          text += ' '
+        # Falling
+        elif a1 == 0 and a2_next == a2 + 1 and a2 != n_moras:
+          text += '↓'
+        # Rising
+        elif a2 == 1 and a2_next == 2:
+          text += '↑'
+    if i<len(marks):
+      text += unidecode(marks[i]).replace(' ','')
+  if re.match('[A-Za-z]',text[-1]):
+    text += '.'
+  return text
 
 
 def korean_cleaners(text):
diff --git a/text/symbols.py b/text/symbols.py
new file mode 100644
index 0000000..95d7390
--- /dev/null
+++ b/text/symbols.py
@@ -0,0 +1,29 @@
+""" from https://github.com/keithito/tacotron """
+
+'''
+Defines the set of symbols used in text input to the model.
+'''
+
+'''# japanese_cleaners
+_pad        = '_'
+_punctuation = ',.!?-'
+_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧ↓↑ '
+'''
+
+'''# japanese_cleaners2
+_pad        = '_'
+_punctuation = ',.!?-'
+_letters = 'AEINOQUabdefghijkmnoprstuvwyzʃʧʦ↓↑ '
+'''
+
+# korean_cleaners
+_pad        = '_'
+_punctuation = ',.!?…~'
+_letters = 'ㄱㄴㄷㄹㅁㅂㅅㅇㅈㅊㅋㅌㅍㅎㄲㄸㅃㅆㅉㅏㅓㅗㅜㅡㅣㅐㅔ '
+
+
+# Export all symbols:
+symbols = [_pad] + list(_punctuation) + list(_letters)
+
+# Special symbol ids
+SPACE_ID = symbols.index(" ")
diff --git a/train.py b/train.py
index 988f1a2..336698e 100644
--- a/train.py
+++ b/train.py
@@ -1,4 +1,3 @@
-from ast import Import
 import os
 import json
 import argparse
@@ -37,7 +36,7 @@
   kl_loss
 )
 from mel_processing import mel_spectrogram_torch, spec_to_mel_torch
-from text import initialize
+from text.symbols import symbols
 
 
 torch.backends.cudnn.benchmark = True
@@ -53,7 +52,6 @@ def main():
   os.environ['MASTER_PORT'] = '80000'
 
   hps = utils.get_hparams()
-  initialize(hps.symbols)
   mp.spawn(run, nprocs=n_gpus, args=(n_gpus, hps,))
 
 
@@ -88,7 +86,7 @@ def run(rank, n_gpus, hps):
         drop_last=False, collate_fn=collate_fn)
 
   net_g = SynthesizerTrn(
-      hps.symbols,
+      len(symbols),
       hps.data.filter_length // 2 + 1,
       hps.train.segment_size // hps.data.hop_length,
       **hps.model).cuda(rank)
diff --git a/train_ms.py b/train_ms.py
index 34aa8ca..35201f3 100644
--- a/train_ms.py
+++ b/train_ms.py
@@ -1,5 +1,10 @@
 import os
+import json
+import argparse
+import itertools
+import math
 import torch
+from torch import nn, optim
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from torch.utils.tensorboard import SummaryWriter
@@ -8,6 +13,7 @@
 from torch.nn.parallel import DistributedDataParallel as DDP
 from torch.cuda.amp import autocast, GradScaler
 
+import librosa
 import logging
 
 logging.getLogger('numba').setLevel(logging.WARNING)
@@ -30,7 +36,7 @@
   kl_loss
 )
 from mel_processing import mel_spectrogram_torch, spec_to_mel_torch
-from text import initialize
+from text.symbols import symbols
 
 
 torch.backends.cudnn.benchmark = True
@@ -46,7 +52,6 @@ def main():
   os.environ['MASTER_PORT'] = '80000'
 
   hps = utils.get_hparams()
-  initialize(hps.symbols)
   mp.spawn(run, nprocs=n_gpus, args=(n_gpus, hps,))
 
 
@@ -81,7 +86,7 @@ def run(rank, n_gpus, hps):
         drop_last=False, collate_fn=collate_fn)
 
   net_g = SynthesizerTrn(
-      hps.symbols,
+      len(symbols),
       hps.data.filter_length // 2 + 1,
       hps.train.segment_size // hps.data.hop_length,
       n_speakers=hps.data.n_speakers,