diff --git a/.circleci/config.yml b/.circleci/config.yml
index 5f6db915..6570bad6 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -25,7 +25,7 @@ jobs:
       - checkout
       - run: |
           sudo apt update
-          sudo apt install espeak git
+          sudo apt install espeak-ng git
       - run: sudo pip install --upgrade pip
       - run: sudo pip install -e .
       - run: |
diff --git a/TTS/bin/find_unique_chars.py b/TTS/bin/find_unique_chars.py
index e6c35878..f9b6827b 100644
--- a/TTS/bin/find_unique_chars.py
+++ b/TTS/bin/find_unique_chars.py
@@ -7,16 +7,15 @@ from TTS.tts.datasets.preprocess import get_preprocessor_by_name
 
 
 def main():
+    # pylint: disable=bad-continuation
     parser = argparse.ArgumentParser(description='''Find all the unique characters or phonemes in a dataset.\n\n'''
 
     '''Target dataset must be defined in TTS.tts.datasets.preprocess\n\n'''\
-
     '''
     Example runs:
 
     python TTS/bin/find_unique_chars.py --dataset ljspeech --meta_file /path/to/LJSpeech/metadata.csv
-    ''',
-        formatter_class=RawTextHelpFormatter)
+    ''', formatter_class=RawTextHelpFormatter)
 
     parser.add_argument(
         '--dataset',
@@ -36,13 +35,13 @@ def main():
 
     preprocessor = get_preprocessor_by_name(args.dataset)
     items = preprocessor(os.path.dirname(args.meta_file), os.path.basename(args.meta_file))
-    texts = " ".join([item[0] for item in items])
+    texts = "".join(item[0] for item in items)
     chars = set(texts)
-    lower_chars = set(texts.lower())
+    lower_chars = filter(lambda c: c.islower(), chars)
     print(f" > Number of unique characters: {len(chars)}")
     print(f" > Unique characters: {''.join(sorted(chars))}")
     print(f" > Unique lower characters: {''.join(sorted(lower_chars))}")
 
 
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()
diff --git a/TTS/bin/train_glow_tts.py b/TTS/bin/train_glow_tts.py
index 9db2381e..a12c5581 100644
--- a/TTS/bin/train_glow_tts.py
+++ b/TTS/bin/train_glow_tts.py
@@ -268,7 +268,7 @@ def train(data_loader, model, criterion, optimizer, scheduler,
             if global_step % c.save_step == 0:
                 if c.checkpoint:
                     # save model
-                    save_checkpoint(model, optimizer, global_step, epoch, 1, OUT_PATH,
+                    save_checkpoint(model, optimizer, global_step, epoch, 1, OUT_PATH, model_characters,
                                     model_loss=loss_dict['loss'])
 
                 # wait all kernels to be completed
@@ -467,7 +467,7 @@ def evaluate(data_loader, model, criterion, ap, global_step, epoch):
 
 def main(args):  # pylint: disable=redefined-outer-name
     # pylint: disable=global-variable-undefined
-    global meta_data_train, meta_data_eval, symbols, phonemes, speaker_mapping
+    global meta_data_train, meta_data_eval, symbols, phonemes, model_characters, speaker_mapping
     # Audio processor
     ap = AudioProcessor(**c.audio)
     if 'characters' in c.keys():
@@ -477,7 +477,10 @@ def main(args):  # pylint: disable=redefined-outer-name
     if num_gpus > 1:
         init_distributed(args.rank, num_gpus, args.group_id,
                          c.distributed["backend"], c.distributed["url"])
-    num_chars = len(phonemes) if c.use_phonemes else len(symbols)
+
+    # set model characters
+    model_characters = phonemes if c.use_phonemes else symbols
+    num_chars = len(model_characters)
 
     # load data instances
     meta_data_train, meta_data_eval = load_meta_data(c.datasets)
@@ -559,7 +562,7 @@ def main(args):  # pylint: disable=redefined-outer-name
         if c.run_eval:
             target_loss = eval_avg_loss_dict['avg_loss']
         best_loss = save_best_model(target_loss, best_loss, model, optimizer, global_step, epoch, c.r,
-                                    OUT_PATH)
+                                    OUT_PATH, model_characters)
 
 
 if __name__ == '__main__':
diff --git a/TTS/bin/train_speedy_speech.py b/TTS/bin/train_speedy_speech.py
index a9a83bbf..1f32c8f6 100644
--- a/TTS/bin/train_speedy_speech.py
+++ b/TTS/bin/train_speedy_speech.py
@@ -247,7 +247,7 @@ def train(data_loader, model, criterion, optimizer, scheduler,
             if global_step % c.save_step == 0:
                 if c.checkpoint:
                     # save model
-                    save_checkpoint(model, optimizer, global_step, epoch, 1, OUT_PATH,
+                    save_checkpoint(model, optimizer, global_step, epoch, 1, OUT_PATH, model_characters,
                                     model_loss=loss_dict['loss'])
 
                 # wait all kernels to be completed
@@ -431,7 +431,7 @@ def evaluate(data_loader, model, criterion, ap, global_step, epoch):
 # FIXME: move args definition/parsing inside of main?
 def main(args):  # pylint: disable=redefined-outer-name
     # pylint: disable=global-variable-undefined
-    global meta_data_train, meta_data_eval, symbols, phonemes, speaker_mapping
+    global meta_data_train, meta_data_eval, symbols, phonemes, model_characters, speaker_mapping
     # Audio processor
     ap = AudioProcessor(**c.audio)
     if 'characters' in c.keys():
@@ -441,7 +441,10 @@ def main(args):  # pylint: disable=redefined-outer-name
     if num_gpus > 1:
         init_distributed(args.rank, num_gpus, args.group_id,
                          c.distributed["backend"], c.distributed["url"])
-    num_chars = len(phonemes) if c.use_phonemes else len(symbols)
+
+    # set model characters
+    model_characters = phonemes if c.use_phonemes else symbols
+    num_chars = len(model_characters)
 
     # load data instances
     meta_data_train, meta_data_eval = load_meta_data(c.datasets, eval_split=True)
@@ -523,7 +526,7 @@ def main(args):  # pylint: disable=redefined-outer-name
             target_loss = eval_avg_loss_dict['avg_loss']
         best_loss = save_best_model(target_loss, best_loss, model, optimizer,
                                     global_step, epoch, c.r,
-                                    OUT_PATH)
+                                    OUT_PATH, model_characters)
 
 
 if __name__ == '__main__':
diff --git a/TTS/bin/train_tacotron.py b/TTS/bin/train_tacotron.py
index 0a53f2a1..a9c0881f 100644
--- a/TTS/bin/train_tacotron.py
+++ b/TTS/bin/train_tacotron.py
@@ -284,6 +284,7 @@ def train(data_loader, model, criterion, optimizer, optimizer_st, scheduler,
                     save_checkpoint(model, optimizer, global_step, epoch, model.decoder.r, OUT_PATH,
                                     optimizer_st=optimizer_st,
                                     model_loss=loss_dict['postnet_loss'],
+                                    characters=model_characters,
                                     scaler=scaler.state_dict() if c.mixed_precision else None)
 
                 # Diagnostic visualizations
@@ -492,9 +493,11 @@ def evaluate(data_loader, model, criterion, ap, global_step, epoch):
 
 def main(args):  # pylint: disable=redefined-outer-name
     # pylint: disable=global-variable-undefined
-    global meta_data_train, meta_data_eval, symbols, phonemes, speaker_mapping
+    global meta_data_train, meta_data_eval, speaker_mapping, symbols, phonemes, model_characters
     # Audio processor
     ap = AudioProcessor(**c.audio)
+
+    # setup custom characters if set in config file.
     if 'characters' in c.keys():
         symbols, phonemes = make_symbols(**c.characters)
 
@@ -503,6 +506,7 @@ def main(args):  # pylint: disable=redefined-outer-name
         init_distributed(args.rank, num_gpus, args.group_id,
                          c.distributed["backend"], c.distributed["url"])
     num_chars = len(phonemes) if c.use_phonemes else len(symbols)
+    model_characters = phonemes if c.use_phonemes else symbols
 
     # load data instances
     meta_data_train, meta_data_eval = load_meta_data(c.datasets)
@@ -634,6 +638,7 @@ def main(args):  # pylint: disable=redefined-outer-name
             epoch,
             c.r,
             OUT_PATH,
+            model_characters,
             scaler=scaler.state_dict() if c.mixed_precision else None
         )
 
diff --git a/TTS/tts/datasets/TTSDataset.py b/TTS/tts/datasets/TTSDataset.py
index 3b327cbc..16329ad7 100644
--- a/TTS/tts/datasets/TTSDataset.py
+++ b/TTS/tts/datasets/TTSDataset.py
@@ -39,6 +39,7 @@ class MyDataset(Dataset):
             compute_linear_spec (bool): compute linear spectrogram if True.
             ap (TTS.tts.utils.AudioProcessor): audio processor object.
             meta_data (list): list of dataset instances.
+            tp (dict): dict of custom text characters used for converting texts to sequences.
             batch_group_size (int): (0) range of batch randomization after sorting
                 sequences by length.
             min_seq_len (int): (0) minimum sequence length to be processed
diff --git a/TTS/tts/utils/io.py b/TTS/tts/utils/io.py
index 63e04283..fe94d98d 100644
--- a/TTS/tts/utils/io.py
+++ b/TTS/tts/utils/io.py
@@ -38,7 +38,15 @@ def load_checkpoint(model, checkpoint_path, amp=None, use_cuda=False, eval=False
     return model, state
 
 
-def save_model(model, optimizer, current_step, epoch, r, output_path, amp_state_dict=None, **kwargs):
+def save_model(model,
+               optimizer,
+               current_step,
+               epoch,
+               r,
+               output_path,
+               characters,
+               amp_state_dict=None,
+               **kwargs):
     """Save ```TTS.tts.models``` states with extra fields.
 
     Args:
@@ -48,6 +56,7 @@ def save_model(model, optimizer, current_step, epoch, r, output_path, amp_state_
         epoch (int): current number of training epochs.
         r (int): model reduction rate for Tacotron models.
         output_path (str): output path to save the model file.
+        characters (list): list of characters used in the model.
         amp_state_dict (state_dict, optional): Apex.amp state dict if Apex is enabled. Defaults to None.
     """
     if hasattr(model, 'module'):
@@ -60,7 +69,8 @@ def save_model(model, optimizer, current_step, epoch, r, output_path, amp_state_
         'step': current_step,
         'epoch': epoch,
         'date': datetime.date.today().strftime("%B %d, %Y"),
-        'r': r
+        'r': r,
+        'characters': characters
     }
     if amp_state_dict:
         state['amp'] = amp_state_dict
@@ -68,7 +78,8 @@ def save_model(model, optimizer, current_step, epoch, r, output_path, amp_state_
     torch.save(state, output_path)
 
 
-def save_checkpoint(model, optimizer, current_step, epoch, r, output_folder, **kwargs):
+def save_checkpoint(model, optimizer, current_step, epoch, r, output_folder,
+                    characters, **kwargs):
     """Save model checkpoint, intended for saving checkpoints at training.
 
     Args:
@@ -78,14 +89,16 @@ def save_checkpoint(model, optimizer, current_step, epoch, r, output_folder, **k
         epoch (int): current number of training epochs.
         r (int): model reduction rate for Tacotron models.
         output_path (str): output path to save the model file.
+        characters (list): list of characters used in the model.
     """
     file_name = 'checkpoint_{}.pth.tar'.format(current_step)
     checkpoint_path = os.path.join(output_folder, file_name)
     print(" > CHECKPOINT : {}".format(checkpoint_path))
-    save_model(model, optimizer, current_step, epoch, r, checkpoint_path, **kwargs)
+    save_model(model, optimizer, current_step, epoch, r, checkpoint_path, characters, **kwargs)
 
 
-def save_best_model(target_loss, best_loss, model, optimizer, current_step, epoch, r, output_folder, **kwargs):
+def save_best_model(target_loss, best_loss, model, optimizer, current_step,
+                    epoch, r, output_folder, characters,  **kwargs):
     """Save model checkpoint, intended for saving the best model after each epoch.
     It compares the current model loss with the best loss so far and saves the
     model if the current loss is better.
@@ -99,6 +112,7 @@ def save_best_model(target_loss, best_loss, model, optimizer, current_step, epoc
         epoch (int): current number of training epochs.
         r (int): model reduction rate for Tacotron models.
         output_path (str): output path to save the model file.
+        characters (list): list of characters used in the model.
 
     Returns:
         float: updated current best loss.
@@ -107,6 +121,6 @@ def save_best_model(target_loss, best_loss, model, optimizer, current_step, epoc
         file_name = 'best_model.pth.tar'
         checkpoint_path = os.path.join(output_folder, file_name)
         print(" >> BEST MODEL : {}".format(checkpoint_path))
-        save_model(model, optimizer, current_step, epoch, r, checkpoint_path, model_loss=target_loss, **kwargs)
+        save_model(model, optimizer, current_step, epoch, r, checkpoint_path, characters, model_loss=target_loss, **kwargs)
         best_loss = target_loss
     return best_loss
diff --git a/TTS/tts/utils/text/__init__.py b/TTS/tts/utils/text/__init__.py
index 23c5ab5f..9771e691 100644
--- a/TTS/tts/utils/text/__init__.py
+++ b/TTS/tts/utils/text/__init__.py
@@ -6,7 +6,7 @@ import phonemizer
 from packaging import version
 from phonemizer.phonemize import phonemize
 from TTS.tts.utils.text import cleaners
-from TTS.tts.utils.text.symbols import (_bos, _eos, _phoneme_punctuations,
+from TTS.tts.utils.text.symbols import (_bos, _eos, _punctuations,
                                         make_symbols, phonemes, symbols)
 
 
@@ -24,7 +24,7 @@ _phonemes = phonemes
 _CURLY_RE = re.compile(r'(.*?)\{(.+?)\}(.*)')
 
 # Regular expression matching punctuations, ignoring empty space
-PHONEME_PUNCTUATION_PATTERN = r'['+_phoneme_punctuations+']+'
+PHONEME_PUNCTUATION_PATTERN = r'['+_punctuations.replace(' ', '')+']+'
 
 
 def text2phone(text, language):
diff --git a/TTS/tts/utils/text/symbols.py b/TTS/tts/utils/text/symbols.py
index 7a741a8f..83435917 100644
--- a/TTS/tts/utils/text/symbols.py
+++ b/TTS/tts/utils/text/symbols.py
@@ -5,6 +5,8 @@ Defines the set of symbols used in text input to the model.
 The default is a set of ASCII characters that works well for English or text that has been run
 through Unidecode. For other data, you can modify _characters. See TRAINING_DATA.md for details.
 '''
+
+
 def make_symbols(characters, phonemes=None, punctuations='!\'(),-.:;? ', pad='_', eos='~', bos='^'):# pylint: disable=redefined-outer-name
     ''' Function to create symbols and phonemes '''
     _symbols = [pad, eos, bos] + list(characters)
@@ -18,15 +20,13 @@ def make_symbols(characters, phonemes=None, punctuations='!\'(),-.:;? ', pad='_'
         _symbols += _arpabet
     return _symbols, _phonemes
 
-
 _pad = '_'
 _eos = '~'
 _bos = '^'
 _characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!\'(),-.:;? '
 _punctuations = '!\'(),-.:;? '
-_phoneme_punctuations = '.!;:,?'
 
-# Phonemes definition
+# Phonemes definition (All IPA characters)
 _vowels = 'iyɨʉɯuɪʏʊeøɘəɵɤoɛœɜɞʌɔæɐaɶɑɒᵻ'
 _non_pulmonic_consonants = 'ʘɓǀɗǃʄǂɠǁʛ'
 _pulmonic_consonants = 'pbtdʈɖcɟkɡqɢʔɴŋɲɳnɱmʙrʀⱱɾɽɸβfvθðszʃʒʂʐçʝxɣχʁħʕhɦɬɮʋɹɻjɰlɭʎʟ'
@@ -41,6 +41,16 @@ symbols, phonemes = make_symbols(_characters, _phonemes, _punctuations, _pad, _e
 # from random import shuffle
 # shuffle(phonemes)
 
+
+def parse_symbols():
+    return {'pad': _pad,
+            'eos': _eos,
+            'bos': _bos,
+            'characters': _characters,
+            'punctuations': _punctuations,
+            'phonemes': _phonemes}
+
+
 if __name__ == '__main__':
     print(" > TTS symbols {}".format(len(symbols)))
     print(symbols)
diff --git a/TTS/utils/arguments.py b/TTS/utils/arguments.py
index 948c90d3..ebacab1b 100644
--- a/TTS/utils/arguments.py
+++ b/TTS/utils/arguments.py
@@ -3,17 +3,16 @@
 """Argument parser for training scripts."""
 
 import argparse
-import re
 import glob
 import os
-
-from TTS.utils.generic_utils import (
-    create_experiment_folder, get_git_branch)
-from TTS.utils.console_logger import ConsoleLogger
-from TTS.utils.io import copy_model_files, load_config
-from TTS.utils.tensorboard_logger import TensorboardLogger
+import re
 
 from TTS.tts.utils.generic_utils import check_config_tts
+from TTS.tts.utils.text.symbols import parse_symbols
+from TTS.utils.console_logger import ConsoleLogger
+from TTS.utils.generic_utils import create_experiment_folder, get_git_branch
+from TTS.utils.io import copy_model_files, load_config
+from TTS.utils.tensorboard_logger import TensorboardLogger
 
 
 def parse_arguments(argv):
@@ -110,38 +109,27 @@ def get_last_checkpoint(path):
 def process_args(args, model_type):
     """Process parsed comand line arguments.
 
-    Parameters
-    ----------
-    args : argparse.Namespace or dict like
-        Parsed input arguments.
-    model_type : str
-        Model type used to check config parameters and setup the TensorBoard
-        logger. One of:
-            - tacotron
-            - glow_tts
-            - speedy_speech
-            - gan
-            - wavegrad
-            - wavernn
+    Args:
+        args (argparse.Namespace or dict like): Parsed input arguments.
+        model_type (str): Model type used to check config parameters and setup the TensorBoard
+            logger. One of:
+                - tacotron
+                - glow_tts
+                - speedy_speech
+                - gan
+                - wavegrad
+                - wavernn
 
-    Raises
-    ------
-    ValueError
-        If `model_type` is not one of implemented choices.
-
-    Returns
-    -------
-    c : TTS.utils.io.AttrDict
-        Config paramaters.
-    out_path : str
-        Path to save models and logging.
-    audio_path : str
-        Path to save generated test audios.
-    c_logger : TTS.utils.console_logger.ConsoleLogger
-        Class that does logging to the console.
-    tb_logger : TTS.utils.tensorboard.TensorboardLogger
-        Class that does the TensorBoard loggind.
+    Raises:
+        ValueError
+            If `model_type` is not one of implemented choices.
 
+    Returns:
+        c (TTS.utils.io.AttrDict): Config paramaters.
+        out_path (str): Path to save models and logging.
+        audio_path (str): Path to save generated test audios.
+        c_logger (TTS.utils.console_logger.ConsoleLogger): Class that does logging to the console.
+        tb_logger (TTS.utils.tensorboard.TensorboardLogger): Class that does the TensorBoard loggind.
     """
     if args.continue_path != "":
         args.output_path = args.continue_path
@@ -156,7 +144,6 @@ def process_args(args, model_type):
 
     # setup output paths and read configs
     c = load_config(args.config_path)
-
     if model_type in "tacotron glow_tts speedy_speech":
         model_class = "TTS"
     elif model_type in "gan wavegrad wavernn":
@@ -192,6 +179,12 @@ def process_args(args, model_type):
         if args.restore_path:
             new_fields["restore_path"] = args.restore_path
         new_fields["github_branch"] = get_git_branch()
+        # if model characters are not set in the config file
+        # save the default set to the config file for future
+        # compatibility.
+        if model_class == 'TTS' and not 'characters' in c:
+            used_characters = parse_symbols()
+            new_fields['characters'] = used_characters
         copy_model_files(c, args.config_path,
                          out_path, new_fields)
         os.chmod(audio_path, 0o775)
diff --git a/TTS/utils/io.py b/TTS/utils/io.py
index 46abf1c8..1148e0fe 100644
--- a/TTS/utils/io.py
+++ b/TTS/utils/io.py
@@ -67,7 +67,7 @@ def copy_model_files(c, config_file, out_path, new_fields):
         if isinstance(value, str):
             new_line = '"{}":"{}",\n'.format(key, value)
         else:
-            new_line = '"{}":{},\n'.format(key, value)
+            new_line = '"{}":{},\n'.format(key, json.dumps(value, ensure_ascii=False))
         config_lines.insert(1, new_line)
     config_out_file = open(copy_config_path, "w")
     config_out_file.writelines(config_lines)
diff --git a/TTS/utils/manage.py b/TTS/utils/manage.py
index 02e515f3..eb57c8be 100644
--- a/TTS/utils/manage.py
+++ b/TTS/utils/manage.py
@@ -128,7 +128,8 @@ class ModelManager(object):
         """Download files from GDrive using their file ids"""
         gdown.download(f"{self.url_prefix}{gdrive_idx}", output=output, quiet=False)
 
-    def _download_zip_file(self, file_url, output):
+    @staticmethod
+    def _download_zip_file(file_url, output):
         """Download the target zip file and extract the files
         to a folder with the same name as the zip file."""
         r = requests.get(file_url)
diff --git a/hubconf.py b/hubconf.py
index 7fc020b5..13549dfe 100644
--- a/hubconf.py
+++ b/hubconf.py
@@ -1,11 +1,11 @@
-dependencies = ['torch', 'gdown', 'pysbd', 'phonemizer', 'unidecode']  # apt install espeak
+dependencies = ['torch', 'gdown', 'pysbd', 'phonemizer', 'unidecode']  # apt install espeak-ng
 import torch
 
 from TTS.utils.synthesizer import Synthesizer
 from TTS.utils.manage import ModelManager
 
 
-def tts(model_name='tts_models/en/ljspeech/tacotron2-DCA', vocoder_name='vocoder_models/en/ljspeech/mulitband-melgan', use_cuda=False):
+def tts(model_name='tts_models/en/ljspeech/tacotron2-DCA', vocoder_name=None, use_cuda=False):
     """TTS entry point for PyTorch Hub that provides a Synthesizer object to synthesize speech from a give text.
 
     Example:
@@ -15,7 +15,7 @@ def tts(model_name='tts_models/en/ljspeech/tacotron2-DCA', vocoder_name='vocoder
 
     Args:
         model_name (str, optional): One of the model names from .model.json. Defaults to 'tts_models/en/ljspeech/tacotron2-DCA'.
-        vocoder_name (str, optional): One of the model names from .model.json. Defaults to 'vocoder_models/en/ljspeech/mulitband-melgan'.
+        vocoder_name (str, optional): One of the model names from .model.json. Defaults to 'vocoder_models/en/ljspeech/multiband-melgan'.
         pretrained (bool, optional): [description]. Defaults to True.
 
     Returns:
@@ -23,8 +23,9 @@ def tts(model_name='tts_models/en/ljspeech/tacotron2-DCA', vocoder_name='vocoder
     """
     manager = ModelManager()
 
-    model_path, config_path = manager.download_model(model_name)
-    vocoder_path, vocoder_config_path = manager.download_model(vocoder_name)
+    model_path, config_path, model_item = manager.download_model(model_name)
+    vocoder_name = model_item['default_vocoder'] if vocoder_name is None else vocoder_name
+    vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name)
 
     # create synthesizer
     synt = Synthesizer(model_path, config_path, vocoder_path, vocoder_config_path, use_cuda)
diff --git a/tests/test_demo_server.py b/tests/test_demo_server.py
index bccff55d..1de3f558 100644
--- a/tests/test_demo_server.py
+++ b/tests/test_demo_server.py
@@ -21,7 +21,7 @@ class DemoServerTest(unittest.TestCase):
         num_chars = len(phonemes) if config.use_phonemes else len(symbols)
         model = setup_model(num_chars, 0, config)
         output_path = os.path.join(get_tests_output_path())
-        save_checkpoint(model, None, 10, 10, 1, output_path)
+        save_checkpoint(model, None, 10, 10, 1, output_path, None)
 
     def test_in_out(self):
         self._create_random_model()
diff --git a/tests/test_text_processing.py b/tests/test_text_processing.py
index 61a83fa1..2ea8e8f9 100644
--- a/tests/test_text_processing.py
+++ b/tests/test_text_processing.py
@@ -19,7 +19,7 @@ def test_phoneme_to_sequence():
     text_hat = sequence_to_phoneme(sequence)
     sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
-    gt = "ɹiːsənt ɹɪsɜːtʃ æt hɑːɹvɚd hɐz ʃoʊn mɛdᵻteɪɾɪŋ fɔːɹ æz lɪɾəl æz eɪt wiːks kæn æktʃuːəli ɪnkɹiːs, ðə ɡɹeɪ mæɾɚɹ ɪnðə pɑːɹts ʌvðə bɹeɪn ɹɪspɑːnsəbəl fɔːɹ ɪmoʊʃənəl ɹɛɡjuːleɪʃən ænd lɜːnɪŋ!"
+    gt = 'ɹiːsənt ɹᵻsɜːtʃ æt hɑːɹvɚd hɐz ʃoʊn mɛdᵻteɪɾɪŋ fɔːɹ æz lɪɾəl æz eɪt wiːks kæn æktʃuːəli ɪŋkɹiːs, ðə ɡɹeɪ mæɾɚɹ ɪnðə pɑːɹts ʌvðə bɹeɪn ɹᵻspɑːnsᵻbəl fɔːɹ ɪmoʊʃənəl ɹɛɡjʊleɪʃən ænd lɜːnɪŋ!'
     assert text_hat == text_hat_with_params == gt
 
     # multiple punctuations
@@ -28,7 +28,7 @@ def test_phoneme_to_sequence():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ?"
+    gt = "biː ɐ vɔɪs, nɑːt æn! ɛkoʊ?"
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -39,7 +39,7 @@ def test_phoneme_to_sequence():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
+    gt = "biː ɐ vɔɪs, nɑːt æn! ɛkoʊ"
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -61,7 +61,7 @@ def test_phoneme_to_sequence():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ."
+    gt = "biː ɐ vɔɪs, nɑːt æn! ɛkoʊ."
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -72,7 +72,7 @@ def test_phoneme_to_sequence():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
-    gt = "^biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ.~"
+    gt = "^biː ɐ vɔɪs, nɑːt æn! ɛkoʊ.~"
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -83,7 +83,7 @@ def test_phoneme_to_sequence():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
+    gt = "biː ɐ vɔɪs, nɑːt æn! ɛkoʊ"
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -97,7 +97,7 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "ɹiːsənt ɹɪsɜːtʃ æt hɑːɹvɚd hɐz ʃoʊn mɛdᵻteɪɾɪŋ fɔːɹ æz lɪɾəl æz eɪt wiːks kæn æktʃuːəli ɪnkɹiːs, ðə ɡɹeɪ mæɾɚɹ ɪnðə pɑːɹts ʌvðə bɹeɪn ɹɪspɑːnsəbəl fɔːɹ ɪmoʊʃənəl ɹɛɡjuːleɪʃən ænd lɜːnɪŋ!"
+    gt = "ɹiːsənt ɹᵻsɜːtʃ æt hɑːɹvɚd hɐz ʃoʊn mɛdᵻteɪɾɪŋ fɔːɹ æz lɪɾəl æz eɪt wiːks kæn æktʃuːəli ɪŋkɹiːs, ðə ɡɹeɪ mæɾɚɹ ɪnðə pɑːɹts ʌvðə bɹeɪn ɹᵻspɑːnsᵻbəl fɔːɹ ɪmoʊʃənəl ɹɛɡjʊleɪʃən ænd lɜːnɪŋ!"
     assert text_hat == text_hat_with_params == gt
 
     # multiple punctuations
@@ -106,7 +106,7 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ?"
+    gt = 'biː ɐ vɔɪs, nɑːt æn! ɛkoʊ?'
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -117,7 +117,7 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
+    gt = 'biː ɐ vɔɪs, nɑːt æn! ɛkoʊ'
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -128,7 +128,7 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn ɛkoʊ!"
+    gt = 'biː ɐ vɔɪs, nɑːt ɐn ɛkoʊ!'
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -139,7 +139,7 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ."
+    gt = 'biː ɐ vɔɪs, nɑːt æn! ɛkoʊ.'
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -150,7 +150,7 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "^biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ.~"
+    gt = "^biː ɐ vɔɪs, nɑːt æn! ɛkoʊ.~"
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
@@ -161,14 +161,14 @@ def test_phoneme_to_sequence_with_blank_token():
     text_hat = sequence_to_phoneme(sequence)
     _ = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters, add_blank=True)
     text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters, add_blank=True)
-    gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
+    gt = "biː ɐ vɔɪs, nɑːt æn! ɛkoʊ"
     print(text_hat)
     print(len(sequence))
     assert text_hat == text_hat_with_params == gt
 
 def test_text2phone():
     text = "Recent research at Harvard has shown meditating for as little as 8 weeks can actually increase, the grey matter in the parts of the brain responsible for emotional regulation and learning!"
-    gt = "ɹ|iː|s|ə|n|t| |ɹ|ɪ|s|ɜː|tʃ| |æ|t| |h|ɑːɹ|v|ɚ|d| |h|ɐ|z| |ʃ|oʊ|n| |m|ɛ|d|ᵻ|t|eɪ|ɾ|ɪ|ŋ| |f|ɔː|ɹ| |æ|z| |l|ɪ|ɾ|əl| |æ|z| |eɪ|t| |w|iː|k|s| |k|æ|n| |æ|k|tʃ|uː|əl|i| |ɪ|n|k|ɹ|iː|s|,| |ð|ə| |ɡ|ɹ|eɪ| |m|æ|ɾ|ɚ|ɹ| |ɪ|n|ð|ə| |p|ɑːɹ|t|s| |ʌ|v|ð|ə| |b|ɹ|eɪ|n| |ɹ|ɪ|s|p|ɑː|n|s|ə|b|əl| |f|ɔː|ɹ| |ɪ|m|oʊ|ʃ|ə|n|əl| |ɹ|ɛ|ɡ|j|uː|l|eɪ|ʃ|ə|n| |æ|n|d| |l|ɜː|n|ɪ|ŋ|!"
+    gt = 'ɹ|iː|s|ə|n|t| |ɹ|ᵻ|s|ɜː|tʃ| |æ|t| |h|ɑːɹ|v|ɚ|d| |h|ɐ|z| |ʃ|oʊ|n| |m|ɛ|d|ᵻ|t|eɪ|ɾ|ɪ|ŋ| |f|ɔː|ɹ| |æ|z| |l|ɪ|ɾ|əl| |æ|z| |eɪ|t| |w|iː|k|s| |k|æ|n| |æ|k|tʃ|uː|əl|i| |ɪ|ŋ|k|ɹ|iː|s|,| |ð|ə| |ɡ|ɹ|eɪ| |m|æ|ɾ|ɚ|ɹ| |ɪ|n|ð|ə| |p|ɑːɹ|t|s| |ʌ|v|ð|ə| |b|ɹ|eɪ|n| |ɹ|ᵻ|s|p|ɑː|n|s|ᵻ|b|əl| |f|ɔː|ɹ| |ɪ|m|oʊ|ʃ|ə|n|əl| |ɹ|ɛ|ɡ|j|ʊ|l|eɪ|ʃ|ə|n| |æ|n|d| |l|ɜː|n|ɪ|ŋ|!'
     lang = "en-us"
     ph = text2phone(text, lang)
     assert gt == ph