mirror of https://github.com/coqui-ai/TTS.git
fixes before first PyPI release
parent
58f6b34f8b
commit
60c1bb93d9
11
README.md
11
README.md
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@ -141,20 +141,21 @@ Some of the public datasets that we successfully applied TTS:
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## Example: Synthesizing Speech on Terminal Using the Released Models.
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## Example: Synthesizing Speech on Terminal Using the Released Models.
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TTS provides a CLI interface for synthesizing speech using pre-trained models. You can either use your own model or the release models under the TTS project.
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After the installation, TTS provides a CLI interface for synthesizing speech using pre-trained models. You can either use your own model or the release models under the TTS project.
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Listing released TTS models.
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Listing released TTS models.
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```./TTS/bin/synthesize.py --list_models```
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```tts --list_models```
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Run a tts and a vocoder model from the released model list. (Simply copy and paste the full model names from the list as arguments for the command below.)
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Run a tts and a vocoder model from the released model list. (Simply copy and paste the full model names from the list as arguments for the command below.)
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```./TTS/bin/synthesize.py --text "Text for TTS" --model_name "<type>/<language>/<dataset>/<model_name>" --vocoder_name "<type>/<language>/<dataset>/<model_name>" --output_path```
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```tts --text "Text for TTS" --model_name "<type>/<language>/<dataset>/<model_name>" --vocoder_name "<type>/<language>/<dataset>/<model_name>" --output_path```
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Run your own TTS model (Using Griffin-Lim Vocoder)
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Run your own TTS model (Using Griffin-Lim Vocoder)
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```./TTS/bin/synthesize.py --text "Text for TTS" --model_path path/to/model.pth.tar --config_path path/to/config.json --out_path output/path/speech.wav```
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```tts --text "Text for TTS" --model_path path/to/model.pth.tar --config_path path/to/config.json --out_path output/path/speech.wav```
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Run your own TTS and Vocoder models
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Run your own TTS and Vocoder models
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```./TTS/bin/synthesize.py --text "Text for TTS" --model_path path/to/config.json --config_path path/to/model.pth.tar --out_path output/path/speech.wav --vocoder_path path/to/vocoder.pth.tar --vocoder_config_path path/to/vocoder_config.json```
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```tts --text "Text for TTS" --model_path path/to/config.json --config_path path/to/model.pth.tar --out_path output/path/speech.wav --vocoder_path path/to/vocoder.pth.tar --vocoder_config_path path/to/vocoder_config.json```
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**Note:** You can use ```./TTS/bin/synthesize.py``` if you prefer running ```tts``` from the TTS project folder.
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## Example: Training and Fine-tuning LJ-Speech Dataset
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## Example: Training and Fine-tuning LJ-Speech Dataset
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Here you can find a [CoLab](https://gist.github.com/erogol/97516ad65b44dbddb8cd694953187c5b) notebook for a hands-on example, training LJSpeech. Or you can manually follow the guideline below.
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Here you can find a [CoLab](https://gist.github.com/erogol/97516ad65b44dbddb8cd694953187c5b) notebook for a hands-on example, training LJSpeech. Or you can manually follow the guideline below.
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@ -23,7 +23,7 @@ def str2bool(v):
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raise argparse.ArgumentTypeError('Boolean value expected.')
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raise argparse.ArgumentTypeError('Boolean value expected.')
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if __name__ == "__main__":
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def main():
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# pylint: disable=bad-continuation
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# pylint: disable=bad-continuation
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parser = argparse.ArgumentParser(description='''Synthesize speech on command line.\n\n'''
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parser = argparse.ArgumentParser(description='''Synthesize speech on command line.\n\n'''
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@ -216,3 +216,7 @@ if __name__ == "__main__":
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out_path = os.path.join(args.out_path, file_name)
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out_path = os.path.join(args.out_path, file_name)
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print(" > Saving output to {}".format(out_path))
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print(" > Saving output to {}".format(out_path))
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synthesizer.save_wav(wav, out_path)
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synthesizer.save_wav(wav, out_path)
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if __name__ == "__main__":
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main()
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@ -9,6 +9,8 @@ Instructions below are based on a Ubuntu 18.04 machine, but it should be simple
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##### Using server.py
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##### Using server.py
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If you have the environment set already for TTS, then you can directly call ```server.py```.
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If you have the environment set already for TTS, then you can directly call ```server.py```.
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**Note:** After installing TTS as a package you can use ```tts-server``` to call the commands below.
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Examples runs:
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Examples runs:
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List officially released models.
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List officially released models.
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39
setup.py
39
setup.py
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@ -33,22 +33,8 @@ args, unknown_args = parser.parse_known_args()
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# Remove our arguments from argv so that setuptools doesn't see them
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# Remove our arguments from argv so that setuptools doesn't see them
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sys.argv = [sys.argv[0]] + unknown_args
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sys.argv = [sys.argv[0]] + unknown_args
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version = '0.0.9'
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version = '0.0.9a0'
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# Adapted from https://github.com/pytorch/pytorch
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cwd = os.path.dirname(os.path.abspath(__file__))
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cwd = os.path.dirname(os.path.abspath(__file__))
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if os.getenv('TTS_PYTORCH_BUILD_VERSION'):
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version = os.getenv('TTS_PYTORCH_BUILD_VERSION')
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else:
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try:
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sha = subprocess.check_output(['git', 'rev-parse', 'HEAD'],
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cwd=cwd).decode('ascii').strip()
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version += '+' + sha[:7]
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except subprocess.CalledProcessError:
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pass
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except IOError: # FileNotFoundError for python 3
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pass
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# Handle Cython code
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# Handle Cython code
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def find_pyx(path='.'):
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def find_pyx(path='.'):
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@ -108,9 +94,11 @@ def pip_install(package_name):
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reqs_from_file = open('requirements.txt').readlines()
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reqs_from_file = open('requirements.txt').readlines()
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# reqs_without_tf = [r for r in reqs_from_file if not r.startswith('tensorflow')]
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# reqs_without_tf = [r for r in reqs_from_file if not r.startswith('tensorflow')]
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# tf_req = [r for r in reqs_from_file if r.startswith('tensorflow')]
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# tf_req = [r for r in reqs_from_file if r.startswith('tensorflow')]
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# requirements = {'install_requires': reqs_without_tf, 'pip_install': tf_req}
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# requirements = {'install_requires': reqs_without_tf, 'pip_install': tf_req}
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with open('README.md', "r", encoding="utf-8") as readme_file:
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README = readme_file.read()
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setup(
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setup(
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name='TTS',
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name='TTS',
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version=version,
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version=version,
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@ -118,8 +106,8 @@ setup(
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author='Eren Gölge',
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author='Eren Gölge',
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author_email='egolge@mozilla.com',
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author_email='egolge@mozilla.com',
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description='Text to Speech with Deep Learning',
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description='Text to Speech with Deep Learning',
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# long_description=README,
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license='MPL-2.0',
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license='MPL-2.0',
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entry_points={'console_scripts': ['tts-server = TTS.server.server:main']},
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ext_modules=find_cython_extensions(),
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ext_modules=find_cython_extensions(),
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packages=find_packages(include=['TTS*']),
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packages=find_packages(include=['TTS*']),
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project_urls={
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project_urls={
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@ -134,17 +122,30 @@ setup(
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},
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},
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install_requires=reqs_from_file,
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install_requires=reqs_from_file,
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python_requires='>=3.6.0',
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python_requires='>=3.6.0',
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entry_points={
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'console_scripts': [
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'tts=TTS.bin.synthesize:main',
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'tts-server = TTS.server.server:main'
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]
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},
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classifiers=[
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classifiers=[
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"Programming Language :: Python",
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"Programming Language :: Python",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3",
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"Programming Language :: Python :: 3.6",
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"Programming Language :: Python :: 3.6",
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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.7",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.8",
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"Programming Language :: Python :: 3.9",
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'Development Status :: 3 - Alpha',
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'Development Status :: 3 - Alpha',
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"Intended Audience :: Science/Research :: Developers",
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"Intended Audience :: Science/Research",
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"Intended Audience :: Developers",
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"Operating System :: POSIX :: Linux",
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"Operating System :: POSIX :: Linux",
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'License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)',
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'License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)',
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"Topic :: Software Development :: Libraries :: Python Modules :: Speech :: Sound/Audio :: Multimedia :: Artificial Intelligence",
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"Topic :: Software Development",
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"Topic :: Software Development :: Libraries :: Python Modules",
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"Topic :: Multimedia :: Sound/Audio :: Speech",
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"Topic :: Multimedia :: Sound/Audio",
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"Topic :: Multimedia",
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"Topic :: Scientific/Engineering :: Artificial Intelligence"
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])
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])
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# for some reason having tensorflow in 'install_requires'
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# for some reason having tensorflow in 'install_requires'
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