* added basic Mary-TTS API endpoints to server
- imported `parse_qs` from `urllib.parse` to parse HTTP POST parameters
- imported `render_template_string` from `flask` to return text as endpoint result
- added new routes:
- `/locales` - returns list of locales (currently locale of active model)
- `/voices` - returns list of voices (currently locale and name of active model)
- `/process` - accepts synth. request (GET and POST) with parameter `INPUT_TEXT` (other parameters ignored since we have only one active model)
* better log messages for Mary-TTS API
- smaller tweaks to log output
* use f-string in log print to please linter
* updated server.py to match 'make style' result
* Fix typo in function definiton
* Swap hasattr out
hasattr(self, "speaker_manager") and hasattr(self, "language_manager") seems to be redundant since BaseTTS defines both.
* Use packaging.version for version comparisons
The distutils package is deprecated¹ and relies on PEP 386² version
comparisons, which have been superseded by PEP 440³ which is implemented
through the packaging module.
With more recent distutils versions, provided through setuptools
vendoring, we are seeing the following exception during version
comparisons:
> TypeError: '<' not supported between instances of 'str' and 'int'
This is fixed by this migration.
[1] https://docs.python.org/3/library/distutils.html
[2] https://peps.python.org/pep-0386/
[3] https://peps.python.org/pep-0440/
* Improve espeak version detection robustness
On many modern systems espeak is just a symlink to espeak-ng. In that
case looking for the 3rd word in the version output will break the
version comparison, when it finds `text-to-speech:`, instead of a proper
version.
This will not break during runtime, where espeak-ng would be
prioritized, but the phonemizer and tokenizer tests force the backend
to `espeak`, which exhibits this breakage.
This improves the version detection by simply looking for the version
after the "text-to-speech:" token.
* Replace distuils.copy_tree with shutil.copytree
The distutils module is deprecated and slated for removal in Python
3.12. Its usage should be replaced, in this case by a compatible method
from shutil.
* Adding neural HMM TTS
* Adding tests
* Adding neural hmm on readme
* renaming training recipe
* Removing overflow\s decoder parameters from the config
* Update the Trainer requirement version for a compatible one (#2276)
* Bump up to v0.10.2
* Adding neural HMM TTS
* Adding tests
* Adding neural hmm on readme
* renaming training recipe
* Removing overflow\s decoder parameters from the config
* fixing documentation
Co-authored-by: Edresson Casanova <edresson1@gmail.com>
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Fixed bug related to yourtts speaker embeddings issue
* Reverted code for base_tts
* Bug fix on VITS d_vector_file type
* Ignore the test speakers on YourTTS recipe
* Add speaker encoder model and config on YourTTS recipe to easily do zero-shot inference
* Update YourTTS config file
* Update ModelManager._update_path to deal with list attributes
* Fix lint checks
* Remove unused code
* Fix unit tests
* Reset name_to_id to get the right speaker ids on load_embeddings_from_list_of_files
* Set weighted_sampler_multipliers as an empty dict to prevent users' mistakes
Co-authored-by: Edresson Casanova <edresson1@gmail.com>
* Add Ukrainian LADA (female) voice
* Add ca and fa models
* Add pth files to manager
* Bump up to v0.10.1
Co-authored-by: Yehor Smoliakov <yehors@ukr.net>
* Adding pretrained Overflow model
* Stabilize HMM
* Fixup model manager
* Return `audio_unique_name` by default
* Distribute max split size over datasets
* Fixup eval_split_size
* Make style
* Add YourTTS VCTK recipe
* Fix lint
* Add compute_embeddings and resample_files functions to be able to reuse it
* Add automatic download and speaker embedding computation for YourTTS VCTK recipe
* Add parameter for eval metadata file on compute embeddings function
* Adding encoder
* currently modifying hmm
* Adding hmm
* Adding overflow
* Adding overflow setting up flat start
* Removing runs
* adding normalization parameters
* Fixing models on same device
* Training overflow and plotting evaluations
* Adding inference
* At the end of epoch the test sentences are coming on cpu instead of gpu
* Adding figures from model during training to monitor
* reverting tacotron2 training recipe
* fixing inference on gpu for test sentences on config
* moving helpers and texts within overflows source code
* renaming to overflow
* moving loss to the model file
* Fixing the rename
* Model training but not plotting the test config sentences's audios
* Formatting logs
* Changing model name to camelcase
* Fixing test log
* Fixing plotting bug
* Adding some tests
* Adding more tests to overflow
* Adding all tests for overflow
* making changes to camel case in config
* Adding information about parameters and docstring
* removing compute_mel_statistics moved statistic computation to the model instead
* Added overflow in readme
* Adding more test cases, now it doesn't saves transition_p like tensor and can be dumped as json