* refactor(punctuation): remove orphan code for handling lone punctuation
The case of lone punctuation is already handled at the top of restore(). The
removed if statement would never be called and would in fact raise an
AttributeError because the _punc_index named tuple doesn't have the attribute
`mark`.
* refactor(punctuation): remove unused argument
* fix(punctuation): correctly handle initial punctuation
Stripping and restoring initial punctuation didn't work correctly because the
string-splitting caused an additional empty string to be inserted in the text
list (because `".A".split(".")` => `["", "A"]`). Now, an initial empty string is
skipped and relevant test cases are added.
Fixes#3333
Previously, the text was wrapped in an additional set of quotes that was passed
to Espeak. This could result in different phonemization in certain edges and
caused the insertion of an initial separator "_" that had to be removed.
Compare:
$ espeak-ng -q -b 1 -v en-us --ipa=1 '"A"'
_ˈɐ
$ espeak-ng -q -b 1 -v en-us --ipa=1 'A'
ˈeɪ
Fixes#2619
* Replaced PyTorch weight_norm With parametrizations.weight_norm
* TorchAudio: Migrating The I/O Functions To Use The Dispatcher Mechanism
* Corrected Code Style
---------
Co-authored-by: Eren Gölge <erogol@hotmail.com>
* Implement most similar ref training approach
* Use non-enhanced hifigan for test samples
* Add Perceiver
* Update GPT Trainer for perceiver support
* Update XTTS docs
* Bug fix masking with XTTS perceiver
* Bug fix on gpt forward
* Bug Fix on XTTS v2.0 training
* Add XTTS v2.0 unit tests
* Add XTTS v2.0 inference unit tests
* Bug Fix on diffusion inference
* Add XTTS v2.0 training recipe
* Placeholder model entry
* Add cloning params to config
* Make prompt embedding configurable
* Make cloning configurable
* Cheap fix for a cheaper fix
* Prevent resampling
* Update model entry
* Update docs
* Update requirements
* Code linting
* Add xtts v2 to sep tests
* Bug fix on XTTS get_gpt_cond_latents
* Bug fix on rebase
* Make style
* Bug fix in Japenese tokenizer
* Add num2words to deps
* Remove unused kwarg and added num_beams=1 as default
---------
Co-authored-by: Eren G??lge <egolge@coqui.ai>
* Don't install MeCab by default
* Add optional [ja] deps, like [dev] etc
* Add JA requirements file
* Add JA requirements to requirements_all
This should help the tests run.
* Draft ONNX export for VITS
Could not get it work to output variable length sequence
* Fixup for onnx constant output
* Make style
* Remove commented code
* initial commit
* Tortoise inference
* revert path change
* style fix
* remove accidental remove
* style fixes
* style fixes
* removed unwanted assests and deps
* remove changes
* remove cvvp
* style fix black
* added tortoise config and updated config and args, refactoring the code
* added tortoise to api
* Pull mel_norm from url
* Use TTS cleaners
* Let download model files
* add ability to pass tortoise presets through coqui api
* fix tests
* fix style and tests
* fix tts commandline for tortoise
* Add config.json to tortoise
* Use kwargs
* Use regular model api for loading tortoise
* Add load from dir to synthesizer
* Fix Tortoise floats
* Use model_dir when there are multiple urls
* Use `synthesize` when exists
* lint fixes and resolve preset bug
* resolve a download bug and update model link
* fix json
* do tortoise inference from voice dir
* fix
* fix test
* fix speaker id and remove assests
* update inference_tests.yml
* replace inference_test.yml
* fix extra dir as None
* fix tests
* remove space
* Reformat docstring
* Add docs
* Update docs
* lint fixes
---------
Co-authored-by: Eren Gölge <egolge@coqui.ai>
Co-authored-by: Eren Gölge <erogol@hotmail.com>
Python 3.11 complains about the mutable default and other members
were already adapted to use the factory, so I expect this line just
went unnoticed until now.
Torch set default value for `return_complex=True` for `torch.stft` method
This turned warning into error:-
```
Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 1591, in fit
self._fit()
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 1544, in _fit
self.train_epoch()
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 1309, in train_epoch
_, _ = self.train_step(batch, batch_num_steps, cur_step, loader_start_time)
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 1162, in train_step
outputs, loss_dict_new, step_time = self._optimize(
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 1023, in _optimize
outputs, loss_dict = self._model_train_step(batch, model, criterion, optimizer_idx=optimizer_idx)
File "/usr/local/lib/python3.10/dist-packages/trainer/trainer.py", line 970, in _model_train_step
return model.train_step(*input_args)
File "/workspace/coqui-tts/TTS/tts/models/vits.py", line 1293, in train_step
mel_slice_hat = wav_to_mel(
File "/workspace/coqui-tts/TTS/tts/models/vits.py", line 191, in wav_to_mel
spec = torch.stft(
File "/usr/local/lib/python3.10/dist-packages/torch/functional.py", line 641, in stft
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
RuntimeError: stft requires the return_complex parameter be given for real inputs, and will further require that return_complex=True in a future PyTorch release.
```
* 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>
* 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
* 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
WeberJulian
Frederico S. Oliveira
Aaron-Li
Eren Gölge
Edresson Casanova
Enno Hermann
Eren G??lge
Aarni Koskela
Matthew Boakes
Gorkem
Aya Jafari
loupzeur
Aleś Bułojčyk
Jake Tae
Javier
logan hart
Paul O'Leary McCann
ZhouGongZaiShi
Tsai Meng-Ting
manmay nakhashi
Michael Görner
Matthew Boakes
Yingzhi WANG
p0p
Khalid Bashir
Roee Shenberg
Daniel Vera Nieto
Dani Vera
thennal10
Martin Weinelt
Gerard Sant Muniesa
Shivam Mehta
Shivam Mehta