README update, set default models for synthesize.py and server.py. Disable verbose for ap init.

README.md

@@ -10,11 +10,11 @@ TTS comes with [pretrained models](https://github.com/mozilla/TTS/wiki/Released-
 [![License](<https://img.shields.io/badge/License-MPL%202.0-brightgreen.svg>)](https://opensource.org/licenses/MPL-2.0)
 [![PyPI version](https://badge.fury.io/py/TTS.svg)](https://badge.fury.io/py/TTS)
 
-:loudspeaker: [English Voice Samples](https://erogol.github.io/ddc-samples/) and [SoundCloud playlist](https://soundcloud.com/user-565970875/pocket-article-wavernn-and-tacotron2)
+📢 [English Voice Samples](https://erogol.github.io/ddc-samples/) and [SoundCloud playlist](https://soundcloud.com/user-565970875/pocket-article-wavernn-and-tacotron2)
 
-:man_cook:  [TTS training recipes](https://github.com/erogol/TTS_recipes)
+👩🏽‍🍳  [TTS training recipes](https://github.com/erogol/TTS_recipes)
 
-:page_facing_up: [Text-to-Speech paper collection](https://github.com/erogol/TTS-papers)
+📄 [Text-to-Speech paper collection](https://github.com/erogol/TTS-papers)
 
 ## 💬 Where to ask questions
 Please use our dedicated channels for questions and discussion. Help is much more valuable if it's shared publicly, so that more people can benefit from it.

TTS/bin/synthesize.py

@@ -35,6 +35,9 @@ def main():
     # list provided models
     ./TTS/bin/synthesize.py --list_models
 
+    # run tts with default models.
+    ./TTS/bin synthesize.py --text "Text for TTS"
+
     # run a model from the list
     ./TTS/bin/synthesize.py --text "Text for TTS" --model_name "<language>/<dataset>/<model_name>" --vocoder_name "<language>/<dataset>/<model_name>" --output_path
 
@@ -67,14 +70,14 @@ def main():
     parser.add_argument(
         '--model_name',
         type=str,
-        default=None,
+        default="tts_models/en/ljspeech/speedy-speech-wn",
         help=
         'Name of one of the pre-trained tts models in format <language>/<dataset>/<model_name>'
     )
     parser.add_argument(
         '--vocoder_name',
         type=str,
-        default=None,
+        default="vocoder_models/en/ljspeech/mulitband-melgan",
         help=
         'Name of one of the pre-trained  vocoder models in format <language>/<dataset>/<model_name>'
     )

TTS/server/server.py

@@ -17,8 +17,8 @@ def create_argparser():
 
     parser = argparse.ArgumentParser()
     parser.add_argument('--list_models', type=convert_boolean, nargs='?', const=True, default=False, help='list available pre-trained tts and vocoder models.')
-    parser.add_argument('--model_name', type=str, help='name of one of the released tts models.')
-    parser.add_argument('--vocoder_name', type=str, help='name of one of the released vocoder models.')
+    parser.add_argument('--model_name', type=str, default="tts_models/en/ljspeech/speedy-speech-wn", help='name of one of the released tts models.')
+    parser.add_argument('--vocoder_name', type=str, default="vocoder_models/en/ljspeech/mulitband-melgan", help='name of one of the released vocoder models.')
     parser.add_argument('--tts_checkpoint', type=str, help='path to custom tts checkpoint file')
     parser.add_argument('--tts_config', type=str, help='path to custom tts config.json file')
     parser.add_argument('--tts_speakers', type=str, help='path to JSON file containing speaker ids, if speaker ids are used in the model')

TTS/utils/synthesizer.py

@@ -79,7 +79,7 @@ class Synthesizer(object):
 
         self.tts_config = load_config(tts_config)
         self.use_phonemes = self.tts_config.use_phonemes
-        self.ap = AudioProcessor(**self.tts_config.audio)
+        self.ap = AudioProcessor(verbose=False, **self.tts_config.audio)
 
         if 'characters' in self.tts_config.keys():
             symbols, phonemes = make_symbols(**self.tts_config.characters)
@@ -96,7 +96,7 @@ class Synthesizer(object):
 
     def load_vocoder(self, model_file, model_config, use_cuda):
         self.vocoder_config = load_config(model_config)
-        self.vocoder_ap = AudioProcessor(**self.vocoder_config['audio'])
+        self.vocoder_ap = AudioProcessor(verbose=False, **self.vocoder_config['audio'])
         self.vocoder_model = setup_generator(self.vocoder_config)
         self.vocoder_model.load_checkpoint(self.vocoder_config, model_file, eval=True)
         if use_cuda: